DRAFT Louisville UTC Report-24March2015

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Louisville Urban
Tree Canopy
Assessment

i

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Acknowledgements
Funding Support: This project was made possible through funding support from Louisville Metro Government and Metro Council, the
Louisville/Jefferson County Metropolitan Sewer District and MSD Board, The Louisville Tree Fund and Louisville Gas and Electric.
Acknowledgments: Special thanks to Mayor Greg Fischer and the following people for their knowledge and time that were instrumental in
completing this project:
Louisville/Jefferson County Information Consortium
Chris Aldredge, Database Administrator
Bruce Carroll, Database Administrator
Louisville/Jefferson County Metropolitan Sewer District
Wes Sydnor, MS4 Program Manager
Louisville Metro Air Pollution Control District
Michelle King, Executive Administrator
Bradley Coomes, Environmental Coordinator
Louisville Metro Government
Maxwell Bradley, Purchasing Supervisor
Maria Koetter, Director of Sustainability
Dr. Mesude Duyar Ozyurekoglu, Metro Parks Forestry Manager
Erin Thompson, Urban Forestry Coordinator
Mary Ellen Wiederwohl, Chief, Louisville Forward

Louisville Metro Tree Advisory Commission (LMTAC)
Henry Heuser, Jr., Co-Chair
Katy Schneider, Co-Chair
Dr. Margaret Carreiro, LMTAC’s Inventory and Scientific
Committee, University of Louisville
Shane Corbin, LMTAC’s Inventory and Scientific Committee,
City of Jefferson, Indiana
Kevin Stellar, LMTAC’s Inventory and Scientific Committee,
Spatial Data Integrations, Inc.
United States Forest Service
Dudley Hartel, Urban Forestry South Center Manager

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ii

Table of Contents
Pg

Section

i Acknowledgements
iii

Executive Summary

01 Introduction
01 Challenges
03 Solutions
04
Why Trees?
05
Study Area
06
Process & Methods
09
10

UTC Results

Overall Findings










Changes Over Time - 11
Canopy By Council District - 13
Canopy By Suburban City - 15
Canopy By Neighborhood - 17
Canopy By Land Use - 19
Special Project Area: SoBro - 21
Socioeconomics - 22

23




31









35

Urban Heat Island

By Land Use - 25
By Suburban City - 26
By Council District - 27
By Neighborhood - 29

Stormwater Management
By Council District - 31
By Sewershed - 33

Ecosystem Health

Pg

Section

39
Canopy Benefits
40

Overall Benefits
43
By Council District
45
By Census Tract
48
Action Plan Development
49

Goals
53 Scenarios
56
Plan Format
57 Prioritization
59 Costs
62
Private and Public Property
64
Recommendations & Next Steps
66

Caring for Existing Trees
67
Planting New Trees
68
Supporting Efforts



Appendix A: Methodologies

Appendix B: Data Tables & Charts

Appendix C: Other Information


References

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iii
Executive
Summary
2015

Louisville UTC: 37%
Louisville UTC minus larger parks: ~30%

Louisville Urban Tree
Canopy Assessment

Residents, businesses and visitors of
Louisville are privileged to be in an area
rich in natural resources and beauty.
Louisville supports a wide diversity of native
woodlands, stately tree-canopied parks and
streets, and expertly landscaped businesses
and residences. Largely due to the high
quality of life and opportunities for success,
Louisville encompasses the most populated
county in Kentucky.
Recently, however, tree canopy loss and
urban heat island effects have become a
concern.
The city’s 2013 Sustain Louisville plan
proposed a variety of actions to reverse
the trend of these issues and challenges by
achieving these important goals:










decrease energy use,
mitigate the risk of climate change
impacts,
achieve and exceed national air quality
standards,
improve waterway quality,
mitigate urban heat island effects,
increase opportunities for active living,
provide nature-based recreation, and
engage the community in sustainability
practices.

The strategies for attaining these goals will
be multi-faceted and long-term, but as a
small or large part of the solutions for each
one of these goals, trees are indeed the
answer. The Sustain Louisville plan identified
the Louisville Metro Tree Advisory’s
recommendation to conduct a countywide
urban tree canopy (UTC) study to determine
the historic and current amount and location

of tree cover, quantify the benefits, set
realistic goals to expand the tree canopy, and
make recommendations for achieving these
goals.

What do we have?
Currently, approximately 37% of the land, or
just over 94,000 acres, in Louisville is covered
by trees. Canopy cover within the “old city
boundary” (before the city-county merger
in 2003) is 26%.
In comparison to other cities and regions, the
tree canopy is higher than Lexington (25%)
and St. Louis (26%), but lower than Cincinnati
(38%) and Nashville (47%). Louisville’s
canopy is also lower than American Forests
recommendation of a 40% overall tree
canopy cover.

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iv

Executive Summary

Much of the tree canopy in Louisville grows in
protected parks, and not directly where people
live and work. Over 13,300 acres of tree canopy are
located in just eight of the largest parks (such as
Jefferson Memorial Forest, the Parklands of Floyd’s
Fork, Iroquois, and Cherokee Park). Excluding
large parks, the urban tree canopy in developed
areas may be closer to 30%.

Figure 1: Changes in
Canopy, 2004 to 2012

Historically, a negative trend has also been
established, as Louisville has lost 7%, or 6,500 acres,
of its trees since 2004. That’s a rate of 820 acres of
canopy or 54,000 trees lost per year. The map at
right (Figure 1) shows the rates of canopy decrease
across Louisville between 2004 and 2012.

40%
in 2004

38%
in 2008

37%

in 2012

Canopy Change
Increase 0%-12%
Decrease 0%-5%

To compound this trend, Louisville will experience
a significant canopy loss due to the exotic pest
emerald ash borer (EAB). Ash trees comprise 10%17% of suburban and rural forests, meaning tens
of thousands of ash trees will be lost in Louisville
within the next five to ten years (UK 2014). Given
the historic trend of tree loss and combined with
the inevitable loss of ash trees from EAB, if no steps
are taken to address canopy levels, Louisville’s tree
canopy will drop to 31% by 2022 and potentially to
21% by 2052. Future canopy projection is shown in
Figure 2.

Decrease 5%-10%
Decrease 10%-15%
Decrease 15%-20%
Decrease >20%

Louisville is losing an average of
820 acres (approximately 54,000
trees) of canopy each year.

Future Canopy Including Ash Loss
2012 Canopy
37%

37%
37%

37%

31%

37%

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Executive Summary
Louisville Future
Given both the threats to and opportunities
Canopy
Estimates
Figure 2.
Louisville’s Estimated
Future Canopy (No Action Taken)
for managing and expanding the tree canopy

v

in Louisville, and all of the ways trees can
help achieve sustainability goals, this UTC
assessment was undertaken to examine tree
canopy in detail. Canopy was accurately
mapped and then analyzed by a multitude
of factors including land use, surface
temperature, and demographics. Additionally
canopy was segmented by council districts,
neighborhoods, suburban cities and
sewersheds.

40%

38%

40%

37%

35%
32%

35%

28%

30%

25%

31%
25%

28%
24%

20%

21%

Year

2052

2042

2032

2022

2012

15%
2008

If current trends hold,
Louisville canopy is
projected to decrease to
31-35% in the next ten
years, dropping to as
low as 21% over the next
forty years.

45%

Future Canopy Including Ash Loss

2004

A prioritized planting plan was also created
to maximize tree benefits in areas of greatest
need. Plantable areas were evaluated based

Future Canopy Based on Existing Trends

50%

Canopy

For the first time, Louisville’s citizens, allied
organizations, and government agencies have
accurate tree canopy data to rely upon and
formulate next steps.

Actual Canopy

28%

vi
on environmental features (proximity to local
waterways, soil type, floodplains, slope, and
forest fragmentation), stormwater issues, and
urban heat island concerns.

Why trees?
Why does knowing how much tree canopy
exists in Louisville matter, and why should
more trees be planted? The answer is
because trees are truly a community’s “green
asset” and an infrastructure component that
provides a tremendous quantity of “ecosystem
services” such as cleaning the air, intercepting
stormwater before it reaches municipal
sewer systems, increasing property values,
absorbing carbon, saving money on energy
costs, and moderating hot temperatures in
urbanized areas.
Louisville’s current canopy provides $330
million in benefits each year. This includes
annually intercepting over 18 billion gallons of
stormwater, removing 150,000 lbs. of carbon
monoxide, 4.3 million lbs. of ozone, 500,000

Louisville trees
provide approximately
$330 million in
benefits annually.

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lbs. of nitrogen dioxide, 600,000 lbs. of sulfur
dioxide, and 1.2 million lbs. of soot, dust and
other particulates that irritate human lungs.
However, if the canopy continues to decrease,
so too will these benefits. And if the trend
is not reversed, the simultaneous decline
in tree canopy and increase in population
and development will cause more problems
for aging, over-burdened infrastructure,
and create real crises in public health and
community livability.

What do we want?
Establishing tree canopy goals is an important
action to ensure that trees, as a valuable
green infrastructure asset, are maintained
at minimum thresholds, even as Louisville
continues to develop.
Louisville’s preliminary goals are “no net loss”
in five years, and increasing overall canopy
to 40% or 45% in future years. The results
from this UTC study will be used together with
local expertise and open dialog to establish
realistic and achievable city-wide goals, as
well as goals for specific areas and land uses.

How do we get there?
Attaining canopy goals involves more than just
planting trees. Maintaining and protecting
the existing tree cover must go hand in hand
with aggressive tree planting to achieve
desired canopy cover. As a result of the UTC
study, Louisville Metro Government and its
citizens now have the statistical data, mapping
analysis, and a prioritized planting plan that
will help focus tree management and tree
planting resources where they are needed
most.
Recommendations for growing and protecting
the tree canopy in Louisville based on the
findings of the UTC study are provided
to inform consensus and promote action.
Thousands of young trees will need to be
planted and thousands of mature trees
will need to be cared for if trees are to be
embraced as a way to reduce stormwater
issues, improve air and water quality, and
reduce the urban heat island effects in
Louisville.

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01
Introduction
2015

Louisville Urban Tree
Canopy Assessment

historical change in land use and tree canopy,
and analyzed canopy with socioeconomic
and geographic variables, as well as surface
temperatures and stormwater runoff.

Trees in the city of Louisville are a major
component of urban infrastructure, providing
more than just aesthetics and shade. They
provide numerous benefits that help address
mounting issues in public health, stormwater,
and energy and pollution management. Like
many cities across the country, Louisville is
facing a number of challenges brought on by
aging infrastructure combined with continued
growth and development. Add to this the
ongoing loss of trees, and the challenges
compound.

Challenges in Louisville

To understand and begin to address these
issues, and at the recommendation of the
Louisville Metro Tree Advisory Commission,
Louisville tasked Davey Resource Group
to perform an Urban Tree Canopy (UTC)
assessment. The assessment determined
the location and quantity of current canopy,
calculated ecosystem services, documented

Louisville is facing a number of major issues:
urban heat island and its effects (both on
human health and comfort and air quality),
water pollution and stormwater flooding, and
the steady loss of trees from extreme weather
events (Ike Windstorm of 2008 and Ohio
Valley Ice storm of 2009), insects and diseases,
development, and lack of tree care.

This report provides an overview of the
UTC process, assessment results, and
recommendations for tree planting and
management strategies.

02

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Challenges

Urban heat measured by satellite in Louisville.
Image Source: Climate Central

Sewer manhole overflow in Louisville.
Image Source: MSD Project Win

Dead ash trees in naturalized area.
Image Source: USFS

Heat and Air Quality

Flooding and Water Pollution

Tree Loss from Insects and Disease

Louisville was recently identified as one of
the top ten fastest growing and most intense
heat islands in the country. Heat islands
have a number of negative effects, including
an increase in summertime peak energy
demand and costs, an increased severity of air
pollution and emissions, and a rise in human
health issues, especially when the temperature
reaches over 90°F. Hotter temperatures help
create dangerous ozone pollution levels that
can trigger asthma attacks, heart attacks, and
other serious health conditions (US EPA 2012).

Rainfall overwhelming Louisville’s aging sewer
system is a major factor for local water pollution
and flooding issues. Combine the aging system
with large increases in stormwater runoff from
concrete and other impervious areas like roads,
and buildings, and the problem compounds.
Louisville’s Metropolitan Sewer District (MSD)
is under an EPA consent decree to reduce
the amount and frequency of discharges from
combined sewer overflows (CSOs) into local
waterways. MSD has invested more than $1.4
billion in system expansion and upgrades,
but problems persist during rainfalls. MSD’s
green infrastructure incentive program intends
to reduce these overflows and improve water
quality through natural means, including using
trees to absorb and intercept rainwater (MSD
2014).

Emerald ash borer (EAB) is present in
Louisville. Ash (Fraxinus spp.) trees represent
10%-17% of all trees across the county,
and unless every ash is treated (which is
unrealistic) this species will disappear in the
next 5 to 10 years (UK 2014). The loss of this
significant portion of canopy will result in
a substantial decline in ecosystem service
benefits, further exacerbating heat island and
stormwater issues. Additionally, land owners
(both public and private) will be burdened
with associated removal costs and liability
issues. Beyond EAB, Louisville trees are also
at risk from other serious pests and diseases,
including Asian long-horned beetle, bacterial
leaf scorch, and thousand canker disease.

03

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Solutions

Solutions from Sustain
Louisville
The Sustain Louisville plan was developed
as part of a multifaceted response to these
challenges and identified a significant need to
reduce the city’s carbon footprint, protect the
environment, ensure the health and wellness of
its citizens, and create a culture of sustainability.
Plan goals identified trees as an effective means
of addressing many of the urban challenges
facing the metropolitan area. A full list of goals
from the plan can be found in Appendix C.
Tree canopy, and the benefits it provides, fits
the “triple bottom line approach of people,
prosperity and the planet” referenced in the
plan. It does so by contributing to public
health improvements, providing quantifiable
economic benefits, and protecting the
environment.
As the quantity and quality of tree canopy
in the city increases, so too do the benefits
that canopy provides. It is because trees are
recognized to provide such substantial benefits
that the Louisville Metropolitan Government
has undertaken this UTC assessment.

photo here

04

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Why Trees?

Why Trees?
It is important for Louisville to look at trees as solutions to modern urban challenges. Trees provide a broad spectrum of environmental,
economic, and social benefits (listed below), many of which are well documented by scientific research and are quantifiable at the community
level. Specific and quantified benefits provided by Louisville’s existing tree canopy are detailed in the Canopy Benefits section of this report.
Prevention of Water Pollution. Aging sewers, struggling

Higher Property Values. Trees can increase residential

Stronger, Positive Communities. Tree-lined streets

to keep up with stormwater during a rainfall, overflow and

property and commercial rental values by average of 7%.

can create stronger social ties. In one study, residents of

pollute nearby waterways. Trees act as mini-reservoirs,

Conversely, values can decline by as much as 20% for

apartment buildings with more trees reported they knew

helping to slow and reduce the amount of rainwater in

properties with no trees (Wolf 2007).

their neighbors better, socialized with them more often,
had stronger feelings of community, and felt safer and

storm drains. 100 mature trees can intercept 100,000
gallons of rainfall per year (USFS 2003).

Successful Business Districts. On average, consumers

better adjusted than did residents of more barren, but

will pay about 11% more for goods in shaded and

otherwise identical areas (Kuo 2001b).

Less Energy Consumption. Trees decrease energy

landscaped business districts

(Wolf 1998b, 1999, and

consumption and moderate local climates by providing

2003). Consumers also feel that the quality of the products

Safer Streets. Traffic speeds and the amount of stress

shade and acting as windbreaks.

is better in business districts having trees (Wolf 1998a).

drivers feel are reduced on tree-lined streets, which also is

Cleaner Air. Trees cleanse atmospheric pollutants

Less Crime. Apartment buildings with high levels of

(chemicals, particles, etc.), produce oxygen, and absorb

greenery had 52% fewer crimes than those without any

carbon dioxide.

trees; and apartment buildings with medium amounts of

Less Noise. Trees help reduce noise levels. A 100-foot

greenery had 42% fewer crimes than those without any

wide densely planted tree buffer will reduce noise by 5-8

trees (Kuo and Sullivan 2001a).

decibels (Bentrup 2008).

Leaves emit water vapor making the ambient temperature

Lower Energy Costs. Trees moderate temperatures in

Wildlife Habitat. Connected urban greenways comprised

lower. Temperature differences of 5-15 degrees can be felt

the summer and winter, saving on heating and cooling

of diverse shade and understory trees provide food,

when walking under tree-canopied streets (Miller 1997).

expenses (North Carolina State Univ. 2012, Heisler 1986).

shelter, and water habitat that help connect wildlife with

Reduced Asthma in Children. Trees improve air quality

Better Health. Studies show individuals with views of or

by trapping and holding a significant percentage (up to

access to greenspace tend to be healthier. Employees

Erosion Prevention. Trees, especially tree roots, helps

60%) of pollen, dust and smoke from the air. (Coder 1996)

experience 23% less sick time and greater job satisfaction,

stabilize hillsides by reinforcing soil shear strength

Studies have shown that children who live on tree-lined

and hospital patients recover faster with fewer drugs

(Kazutoki and Ziemer 1991).

streets have lower rates of asthma (Lovasi 2008).

(Ulrich 1984). Trees have also shown to have a calming and

likely to reduce road rage/aggressive driving (Wolf 1998a,

Temperature Moderation. Ever wonder why it always

Kuo and Sullivan 2001b).

feels cooler in or near the woods? It’s not just due to shade.

fragmented urban forests.

healing effect on ADHD adults and teens (Burden 2008).

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Study Area

About the Study Area
Urban tree canopy was examined across all of Louisville. The City of Louisville encompasses
all of Jefferson County, spanning approximately 398 square miles (254,720 acres) across north
central Kentucky, and is bordered in the west by the Ohio River.

Junction of Waterson & I-71
Image Source: Dr. Keith Mountain

06

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Methods

Process & Methods
Louisville’s UTC assessment followed these steps: existing and historic canopy coverage was determined using aerial imagery1, and ecosystem
services provided by current canopy was calculated. An assessment of realistic locations for potential canopy increases was then made by
eliminating impervious areas, water bodies, etc., from possible planting areas. The potential planting areas were prioritized to provide a way for
achieving canopy goals efficiently. Finally a summary report was written and all data files were delivered to Louisville Metropolitan Government
for future use and analysis. Further details on each of these steps and methods are described throughout this report and detailed in the
Further details on each of these steps and methods are highlighted throughout this report and detailed in the appendices.
appendices.

Obtain & 
Analyze
Existing Canopy 
Coverage & 
Benefits

Determine
Possible 
Canopy 
Coverage

Discuss Canopy
Goal Options

Prioritize 
Potential 
Planting Areas 
to Achieve 
Goals

Develop Planting 
Plan and 
Recommendations

Written Report
Electronic Data

This study used a combination of data sources, tools and analysis methods, including USDA aerial imagery (NAIP), third parties for accuracy
Methods. This study used a combination of data sources, tools and analysis methods, including USDA aerial imagery, third parties for
assessments, remote sensing technology, census data, locally-supplied data, other scientific studies and more. These sources will be briefly
accuracy assessments, remote sensing technology, census data, locally-supplied data, other scientific studies and more. These sources will
referenced
throughoutthroughout
this reportthis
andreport
detailed
the appendix.
be briefly referenced
andindetailed
in the appendix.

UTC Results
NAIP imagery (National Agriculture Imagery Program) from the summer growing seasons of 2012, 2008 and 2004.
An
urban tree canopy assessment produces a significant amount of data. These findings are highlighted in the following sections, while
data has been provided electronically to the Louisville Metropolitan Government for further analysis.
1

The most widely used statistics is the overall canopy coverage percentage. Louisville is also fortunate enough to have access to imagery
from 2004 and 2008, allowing discover of canopy change rates as well. Once an overall canopy is determined, this data can be broken

07

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photo here

Country club north of Bowman Field
Image Source: Dr. Keith Mountain

UTC RESULTS
Louisville Urban Tree Canopy Assessment

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09
UTC Results
2015

Louisville Urban Tree
Canopy Assessment

Based on the most recent aerial imagery
(2012), Louisville’s tree canopy covers
37% (just over 94,000 acres) of the entire
county. Excluding large parks, the urban
tree canopy in developed areas is closer
to 30%. Canopy cover within the old city
boundary (before the city-county merger in
2003) is 26%.
In comparison to other cities and regions,
the tree canopy is higher than Lexington
(25%) and St. Louis (26%), but lower than
Cincinnati (38%) and Nashville (47%),
as shown in Table 1. Louisville’s canopy
is also lower than American Forests
recommendation of 40% overall UTC.
Tree canopy is considered one of five land
cover classifications, along with grass/low
vegetation, impervious surfaces (concrete,
buildings, and roads), bare soil and bodies
of water. Figure 3 illustrates land cover as of
2012 in Louisville along with an explanation
of each classification.

Once overall canopy is determined, this
data can be broken down into useful
segments and examined further to
identify trends, including canopy by
multiple political boundaries (council
districts, neighborhoods, and suburban
cities), as well as by categories of land
use, the type of problems occurring
(flooding, excessive heat) and exploring
correlations with the people who reside/
work throughout the metropolitan area
(socioeconomics and demographics).
Louisville’s urban tree canopy assessment
produced a significant amount of data.
The findings of the UTC assessment are
highlighted in the following sections,
while data and GIS files have been
provided electronically to the Louisville
Metropolitan Government for future use
and analysis.

Table 1. City Comparisons
CITY COMPARISONS
CITYdoes
COMPARISONS:
How
How
Louisville/Jefferson
County’s
does
Louisville’s
overall
urban
overall urban tree canopy coverage
compare
regionally?
tree canopy
coverage compare

regionally?

Charlotte, NC *
Nashville, TN *
Pittsburgh, PA

Canopy
Cover

Study
Area

Date
Reported

49%

298 mi2

2012

47%

475 mi

2

2010

42%

2

58 mi

Knoxville, TN

40%

103 mi

Recommended**

40%

-

Cincinnati, OH
Louisville, KY*
Evansville, IN
St. Louis, MO
Lexington , KY

38%

78 mi

2011

2

2014
-

2

2011
2

37%

398 mi

26%

44 mi

2

2011

96 mi

2

2010

85 mi

2

2014

26%
25%

* Study area spans city & surrounding county.
** Recommended canopy by American Forests

2014

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10

Overall Findings
Figure 3. Louisville 2012 Land Cover
Water Bare Soil
(2%)
(4%)
Impervious
(22%)

Canopy
(37%)

Low Veg.
(35%)

Tree Canopy – 37%
Trees’ leaf-covered branches, as seen from above.
Grass/Low Vegetation– 35%
Parks, golf courses, fields, lawns.
Water – 4%
All bodies of water including lakes, ponds, rivers
and streams.

Impervious Surfaces –22%
Roads, sidewalks, buildings, parking lots - all areas where water
cannot soak into the ground.
Bare Soil – 2%
All open areas like sports fields, vacant lots, and construction sites.

("Other Pervious")
Bare Soil

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11

0%

2%

0%

0%

0%

0%

0%

0%

Changes Over Time

Changes Over Time

Table
2. Canopy and Other Land Cover Changes, 2004-2012
OVERALL

Louisville is fortunate to have access to multiple
years (2004, 2008 and 2012) of canopy and
land cover data, allowing unique and valuable
insights into where canopies are changing and
why.
The UTC analysis revealed that tree canopy
in Louisville has decreased from 40% in
2004 to 37% in 2012 as shown in the Table 2,
constituting a 7%* change between 2004 and
2012. This equates to a loss of approximately
6,500 acres of tree canopy, averaging 820 acres
of tree canopy loss per year, or 54,000 trees per
year (assuming a 29-ft crown diameter).

40%
in 2004

38% 37%
in 2008

in 2012

Decreases in canopy cover can often be
attributed to increases in roads and buildings
(impervious land cover) from development.
Such appears to be the case in Louisville.
Between 2004 and 2012, while canopy
decreased, impervious land cover increased by
15%.
The rate of tree canopy loss between the first
four years (2004 to 2008) was higher than
the rate between the latter four years (2008

Year
2004

Year
2008

Year
2012

Rate of
Change *

Tree Canopy

40%

38%

37%

-7%

Buildings, Sidewalks, Roads, etc.
(“Impervious”)

30%

31%

35%

15%

Grass/Low-Lying Vegetation
("Other Pervious")

20%

21%

22%

9%

Bare Soil

4%

4%

4%

0%

Water

6%

6%

2%

-65%

Note: Rates of change were calculated on the canopy to the nearest hundredth of a percent, then
rounded to the nearest whole percentage number.

to 2012). Decreases in canopy cover can
often be attributed to increases in roads and
buildings (impervious land cover). Between
2004 and 2012, while canopy decreased,
impervious land cover increased by
15%. The same period shows a 9% increase
in the grass/low-lying vegetation land
cover (all pervious areas excluding canopy)
which may be attributed to certain types of
development such as new recreational and
other open spaces like sports fields, etc., but
further research would be required to pinpoint
specific drivers of these changes.

Louisville has lost
approximately 6,500
acres of canopy since
2004, averaging 820
acres or 54,000 trees
per year.

* Rate of Change in this report is determined as a percentage, comparing old values to current values using the following equation:
For example, if a park had 46 trees in 2004, and only 42 trees in 2012, that constitutes a -10% change.

current value - older value
x 100
older value

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12

Changes Over Time
Figure 4. Rates of Canopy Change, 2004-2012 (shown by census tract)

Changes in canopy were examined within
each census tract. Of the 191 tracts in the
study area, 179 tracts (94% of all tracts)
experienced a loss of canopy since 2004, as
shown in Figure 4.
Tract 118 (point 1 on map) experienced
the greatest canopy loss with a 31% drop,
and 15 tracts experienced a 20% or greater
drop in canopy (shown in darkest red on
map).

2

Eight census tracts located in the downtown
area and the southwest corner of the county
experienced a gain in UTC (shown in green
on map).
Tract 30 (point 2 on map) experienced the
largest percent canopy gain (12% growth)
with UTC cover increasing from 13% in
2004 and 2008 to 15% in 2012.
A full list of canopy by census tract
has been provided to Louisville Metro
Government electronically.

1

13

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Canopy by Council District

By Council District

Table 3. Historic and Current UTC by Council District

Current and past canopy cover segmented by the 26
council districts can been seen in Table 3 and Figure 5.
Council District 20 has the highest UTC percentage,
followed by Districts 13, 14, and 25.
Districts with the greatest amount of canopy hold some
of the larger parks and naturalized areas in Louisville.
Districts 4, 6 and 21 had the lowest UTC.

Figure 5. Canopy
by Council District

District 1
District 2
District 3
District 4
District 5
District 6
District 7
District 8
District 9
District 10
District 11
District 12
District 13
District 14
District 15
District 16
District 17
District 18
District 19
District 20
District 21
District 22
District 23
District 24
District 25
District 26

Size
(Acres)
9,389
4,986
4,537
4,153
5,371
3,291
7,956
4,322
6,515
6,410
7,032
8,402
20,928
18,013
4,316
16,158
8,916
7,406
19,935
39,330
7,143
12,991
7,988
6,972
7,702
4,160

% of
Study
Area
4%
2%
2%
2%
2%
1%
3%
2%
3%
3%
3%
3%
8%
7%
2%
6%
4%
3%
8%
15%
3%
5%
3%
3%
3%
2%

2004
Canopy
30%
26%
23%
13%
25%
20%
45%
45%
37%
30%
34%
31%
50%
47%
33%
43%
39%
31%
43%
53%
19%
38%
37%
31%
48%
28%

2008
Canopy
28%
23%
23%
12%
23%
19%
42%
43%
35%
28%
33%
29%
48%
46%
32%
42%
38%
29%
41%
52%
17%
37%
36%
30%
46%
27%

2012
Canopy
27%
22%
21%
12%
23%
18%
40%
40%
33%
25%
32%
29%
48%
46%
31%
40%
36%
27%
39%
51%
16%
35%
34%
29%
45%
24%

Rate of
Change
-9%
-14%
-9%
-4%
-6%
-12%
-11%
-12%
-11%
-16%
-6%
-5%
-4%
-1%
-6%
-7%
-9%
-10%
-8%
-3%
-17%
-8%
-8%
-7%
-8%
-14%

Note: Rates of change were calculated on the canopy to the nearest hundredth of a percent, then rounded
to the nearest whole percentage number.

FINAL DRAFT

14

Canopy by Council District
Figure 6. Rates of Canopy Change between 2004-2012 (shown by council district)

¯

Indiana
Oldham

Ohio
R

iver

Clark

Floyd

o

3

19

18
8

15

26
Jefferson

10

11

21
2

20

12
24

25

Harrison

Shelby

9

6

hi
O

17

7
4

r
ve 1
Ri

District 21 had the greatest canopy loss
(a decrease of 17%) with District 14
experiencing the smallest drop of 1%.

16

5

23

22

13

14

Percent Change
Canopy Decrease 0% - 5%
Canopy Decrease 5% - 10%

Hardin

Spencer

Bullitt

Kentucky

Canopy Decrease 10% - 15%
Canopy Decrease > 15%

Every council district experienced a
loss of tree canopy over the eight-year
period, as shown in Figure 6. Over onethird of council districts experienced
double-digit losses.

Nelson

FINAL DRAFT

15

Canopy by Suburban City

HIGHEST Canopy
Decrease
Bellemeade
Meadow Vale
Woodlawn Park
Worthington Hills
Beechwood Village
Rolling Hills
Richlawn
Watterson Park
Coldstream
South Park View*
City of Shively

Image Source: Erin Thompson

Size
(Acres)
180
117
161
158
177
121
65
919
141
77

2004
Canopy

2008
Canopy

2012
Canopy

Rate of
Change

50%
33%
40%
39%
48%
33%
53%
24%
32%
64%*

40%
27%
35%
38%
41%
25%
48%
21%
23%
7%*

36%
23%
28%
28%
33%
23%
34%
15%
19%
28%*

-28%
-29%
-30%
-30%
-31%
-31%
-36%
-37%
-41%
-55%

Table 4. Ten Highest / Ten
Lowest UTC by Suburban City

Highest Canopy

Canopy was also segmented by the 83
suburban cities (outside the old city
boundary) within
the study
area. The Size
LEAST
Canopy
canopy cover within
all suburban cities
Decrease
(Acres)
combined is 31%. The ten cities with the
Heritage Creek
292
greatest and least amount of UTC cover are
West Buechel
412
listed in Table 4.
Green Spring
168
Murray Hill
85
All but two of the 83 cities experienced
Prospect
2,514
a loss of tree canopy in the eight-year
Hills and Dales
64
Riverwood
132
Hollyvilla
219
Indian Hills
1,252
Cambridge
35

time frame. The highest loss occurred in
South Park View (-55%), Cold Stream (-41%)
and Watterson Park (-37%). The two cities
reporting a gain in canopy were Heritage
Creek (+24%) and West Beuchel (+9%).
Rate of
2004
2008
2012
These and other data on canopy change can
Canopy Canopy Canopy Change
be see in Table 5.
24%
19%
23%
24%
9%
10%
11%
11%
A full list with detailed data for all suburban
-2%
50%
49%
49%
cities is available in Appendix B.
-3%
47%
47%
46%
-3%
41%
41%
40%
-3%
57%
56%
55%
-4%
58%
57%
56%
-5%
60%
59%
57%
-5%
67%
67%
64%
-6%
51%
51%
48%

Lowest Canopy

By Suburban City

Municipality
Suburban
City
Mockingbird Valley
Ten Broeck
Indian Hills
Glenview
Hollyvilla
Brownsboro Farm
Anchorage
Riverwood
Druid Hills
Hills and Dales

Canopy %
70%
69%
64%
60%
57%
57%
57%
56%
56%
55%

Municipality
Suburban
City
Langdon Place
Hickory Hill
Shively
Parkway Village
Lynnview
Coldstream
Sycamore
Watterson Park
Poplar Hills
West Buechel

Canopy %
23%
22%
22%
21%
19%
19%
17%
15%
13%
11%

FINAL DRAFT

16

Canopy by Suburban City

Heritage Creek
West Buechel
Green Spring
Murray Hill
Prospect
Hills and Dales
Riverwood
Hollyvilla
Indian Hills
Cambridge
HIGHEST Canopy
Decrease
Bellemeade
Meadow Vale
Woodlawn Park
Worthington Hills
Beechwood Village
Rolling Hills
Richlawn
Watterson Park
Coldstream
South Park View*

Size
(Acres)
292
412
168
85
2,514
64
132
219
1,252
35

2004
Canopy

2008
Canopy

2012
Canopy

Rate of
Change

19%
10%
50%
47%
41%
57%
58%
60%
67%
51%

23%
11%
49%
47%
41%
56%
57%
59%
67%
51%

24%
11%
49%
46%
40%
55%
56%
57%
64%
48%

24%
9%
-2%
-3%
-3%
-3%
-4%
-5%
-5%
-6%

Size
(Acres)
180
117
161
158
177
121
65
919
141
77

2004
Canopy

2008
Canopy

2012
Canopy

Rate of
Change

50%
33%
40%
39%
48%
33%
53%
24%
32%
64%*

40%
27%
35%
38%
41%
25%
48%
21%
23%
7%*

36%
23%
28%
28%
33%
23%
34%
15%
19%
28%*

-28%
-29%
-30%
-30%
-31%
-31%
-36%
-37%
-41%
-55%

Note: Rates of change were calculated on the canopy to the nearest hundredth of a percent, then
rounded to the nearest whole percentage number.

Mockingbird
Valley
70%
* South Park
View’s canopy
Aerial view of South
experienced
some interesting
Ten Broeck
69%
Park View, 2004-2012
changes Indian
between
2004 and
Hills
64%
2004
2012, varying
from
64%
Glenview
60%
in 2004 to
7% in 2008 and
Hollyvilla
57%
back up Brownsboro
to 28% in 2012
(see
Farm
57%
Table 5).Anchorage
This was significant
57%
change over
a
short
period
Riverwood
56%
of time and
warranted
further
Druid Hills
56%
examination.
LandDales
(shown in
Hills and
55%
2008
images at right) appears to
have been
cleared between
Municipality
Canopy %
2004 andLangdon
2008, then
left
to
Place
23%
regenerate between 2008
Hickory Hill
22%
and 2012. The most recent
Shively
22%
images show regenerated
Parkway Village
21%
of trees (darker green color
2012
Lynnview
19%
in 2012 image) that were tall
Coldstream
19%
enough to be considered
Sycamore
17%
tree canopy (as opposed to
Watterson Park
15%
low-lying vegetation) during
Poplar Hills
13%
classification of the 2012
West Buechel
11%
imagery.

Highest Canopy

LEAST Canopy
Decrease

Using Both Percentage and
Acreage
Municipality
Canopy %

Lowest Canopy

Table 5. Rates of Change in Canopy by Suburban City

Large variations in canopy coverage are not uncommon when
dealing with smaller areas like South Park View (77 acres),
so it is important to consider acreage of canopy as well as
canopy cover percent.

FINAL DRAFT

17

Canopy by Neighborhood

By Neighborhood

Figure 7. Neighborhood Canopy

Lowest Canopy

Highest Canopy

The 78 neighborhoods within the old city
boundaries of Louisville have a combined
canopy cover of 26%.
Neighborhood
Canopy %
Iroquois
Park
Generally,
neighborhoods
with the68%
greatest
Cherokee
Seneca
55%
amount of UTC are home to some of the larger
Cherokee
Gardens
53% while
parks and
naturalized
areas in Louisville,
Brownsboro
Zorn
51%
neighborhoods
with the
least amount
of UTC
Audubon and
Parkairport-related
48%
contain industrial
areas. Table
6 lists theKenwood
five neighborhoods
with 45%
the highest
Hill
and lowest
UTC cover,
the map in Figure
Seneca
Gardens
44% 7 shows
neighborhood
Poplarcanopy
Level rates graphically.
42%
Cherokee Triangle
41%
TableBonnycastle
6: Five Highest / Five
41%

Highest

Lowest UTC by Neighborhood
Neighborhood
Iroquois Park
Cherokee Seneca
Cherokee Gardens
Brownsboro Zorn
Audubon Park

Neighborhood
Canopy %
Paristown Pointe
14%
South Louisville
13%
California
13%
Algonquin
12%
Highland Park
12%
University
11%
Neighborhood
Phoenix Hill
11%
Central Business District 8%
Fairgrounds
6%
Standiford
3%

Canopy Change Rates

Canopy %
68%
55%
53%
51%
48%

Lowest

Under 10%

Neighborhood
University
Phoenix Hill
Central Bus. District
Fairgrounds
Standiford

Canopy %
11%
11%
8%
6%
3%

10% - 20%
21-30%
31-40%
Over 40%

FINAL DRAFT

18

Canopy by Neighborhood
Every neighborhood experienced a decrease in
tree canopy between 2004 and 2012 except for three
urban core areas: the Central Business District (+16%),
Russell (no change), and Fairgrounds (no change).
Edgewood experienced the largest decline in UTC in
the eight-year period (-51%), followed by Tyler Park
(-24%). Table 7 lists the five neighborhoods with the
highest and lowest change rates of UTC, while canopy
change rates are shown graphically in Figure 8. A full
table of canopy data for each neighborhood can be
found in Appendix B.

Figure 8. Rates of Change in Canopy by
Neighborhood (2004-2012)

LEAST Canopy
Decrease by
Neighborhood
Central Bus. Dist.
Russell
Fairgrounds
Wyandotte
Wilder Park
Highland Park
Jacobs
Iroquois Park
Portland
South Louisville

Size
(Acres)
758
898
693
348
237
375
451
878
1,609
496

HIGHEST Canopy
Size
Decrease by
(Acres)
Neighborhood
Meadowview Estates
41
Cloverleaf
464
Avondale Melbourne Heights
310
California
787
Strathmoor Manor
36
Phoenix Hill
373

2004
Canopy

2008
Canopy

2012
Canopy

Rate of
Change

7%
21%
6%
26%
30%
12%
23%
71%
26%
14%

7%
20%
6%
27%
31%
13%
24%
70%
24%
14%

8%
21%
6%
25%
29%
12%
22%
68%
25%
13%

16%
0%
0%
-2%
-2%
-2%
-2%
-4%
-4%
-5%

2004
Canopy

2008
Canopy

2012
Canopy

Rate of
Change

41%
28%
37%
16%
51%
14%

40%
26%
35%
14%
46%
11%

34%
23%
29%
13%
39%
11%

-18%
-20%
-20%
-21%
-22%
-22%

Table 7. Rates of Change in Canopy by
Neighborhood
Size

Least Canopy
Decrease
Central Bus. Dist.
Russell
Fairgrounds
Wyandotte
Wilder Park

2004
2008
2012
Rate of
(Acres) Canopy Canopy Canopy Change

Highest Canopy
Decrease
Phoenix Hill
Standiford
Wellington
Tyler Park
Edgewood

Rate of
2004
2008
2012
Change
(Acres) Canopy Canopy Canopy

758
898
693
348
237

7%
21%
6%
26%
30%

7%
20%
6%
27%
31%

8%
21%
6%
25%
29%

16%
0%
0%
-2%
-2%

Size

373
175
57
329
476

14%
4%
32%
48%
33%

11%
4%
28%
48%
21%

11%
3%
25%
37%
16%

Note: Rates of change were calculated on the canopy to the nearest hundredth of a percent,
then rounded to the nearest whole percentage number.

-22%
-23%
-23%
-24%
-51%

19

FINAL DRAFT

Canopy by Land Use

By Land Use
Canopy coverage was analyzed
by nine basic classes of land
use (as defined by the county
property valuator at the parcel
level): commercial, singlefamily residential, multi-family
residential, industrial, public/
semi-public, parks, rights-ofway, farmland, and vacant land.
Additionally, the net gain or loss
of actual acres of canopy over the
eight -year period was calculated
for each land class. Resulting
canopy data by each land class is
shown in Table 8.
All nine land use categories
experienced a drop in canopy,
with a total canopy loss of over
6,500 acres from 2004 to 2012.
As of 2012, the highest
percentages of tree canopy

Over half of all
canopy acreage
lost occurred on
single-family
residential land.

Table 8. Change in Canopy by Land Use

Canopy %
Rights-of-Way
Industrial
Commercial
Residential – Single-Family
Residential – Multi-Family
Public / Semi-Public
Vacant Land
Parks / Open Space
Farmland

Canopy Acres
Residential - Single Family

Acreage in
Study Area
(as of 2012)
31,335
17,556

Percent of
Study Area
(as of 2012)
13%
7%

15,011
82,721
7,971
17,114
18,742
25,887
30,082

6%
34%
3%
7%
8%
11%
12%

246,418

100%

Acreage in
Study Area
(as of 2012)
82,721

Percent of
Study Area
(as of 2012)
34%
13%
8%

Rights-of-Way
Vacant Land

31,335
18,742

Public / Semi-Public
Industrial
Farmland
Parks & Open Space
Commercial
Residential – Multi-Family

17,114
17,556
30,082
25,887
15,011
7,971
246,418

7%
7%
12%
11%
6%
3%
100%

Canopy Cover %
2004
2008
2012
19%
22%
21%
15%
17%
16%
16%
46%
24%
34%
63%
59%
52%

15%
44%
23%
33%
61%
58%
51%

15%
42%
22%
32%
61%
58%
51%

Acres of Canopy
2004
2008
2012
37,795
36,402
34,500

Rate of
Change
-15%
-12%
-9%
-8%
-8%
-7%
-4%
-1%
-1%

Change
in Acres
-3,295

6,988
11,889

6,603
11,506

6,093
11,364

-896
-525

5,896
2,996
15,514
15,193
2,466
1,907
100,644

5,617
2,770
15,428
15,070
2,311
1,819
97,526

5,418
2,677
15,217
14,912
2,195
1,732
94,106

-478
-320
-297
-281
-271
-175
-6,538

Note: Rates of change were calculated on the canopy to the nearest hundredth of a percent, then
rounded to the nearest whole percentage number.

20

FINAL DRAFT

Canopy by Land Use

occurred on vacant land (61%), parks and open
space (58%), and farmland (51%). Rights-ofway (19%), industrial (15%), and commercial
(15%) contain the lowest tree canopy coverage
percentages.
The largest and most predominant land use
category in the 2012 study area, as is evident
in the land use map (Figure 9), is single family
residential (encompassing 34% of the entire
area) with a 42% UTC (down from 46% in 2004).

Figure 9. 2012 Land Use

Though this category did not experience the
highest percentage change compared to other
categories, it accounts for over half of all acres
of canopy loss (3,295 acres lost). Because
trees in residential areas provide the greatest
direct benefits to people in terms of energy
conservation, human health, and property value,
the reason for canopy loss - whether from land
development and/or the decline of mature trees
due to pests or lack of proper maintenance - is
significant and warrants further investigation.

The greatest
opportunities
for canopy
gains will come
through efforts
on privatelyheld lands.
Commercial
Farmland
Industrial
Residential, Multi-Family
Parks / Open Space
Public / Semi Public
Rights of Way
Residential, Single Family
Vacant

The land use category that experienced the
most significant change rate was rights-ofway with a drop of 15% over time, from 22%
in 2004 to 19% in 2012, equaling a loss of
896 acres of canopy. This tree loss occurred
primarily on both residential streets and
state routes, as interstate rights-of-way
comprise a lower proportion of the total
rights-of-way acreage.
Commercial and industrial categories
reported the lowest 2012 tree canopy
coverage (15%). Current research has
demonstrated that business districts are
more successful with tree canopies (detailed
in the Why Trees section).
Based on canopy acres, publicly controlled
land (public/semi public, rights-of-way and
parks/open space land uses) comprises
31% of all land and makes up 28% of
Louisville’s total canopy, while privately
owned land comprises 69% of all land use
and carries the remaining 72% of canopy
cover. So while significant improvement
to Louisville’s tree cover can be made by
planting on public property, the greatest
opportunities for substantial and long-term
canopy gains will come through efforts on
privately-held lands.

21

FINAL DRAFT

South Broadway

Special Project Area: SoBro

SoBro has a UTC of 9% overall (21
acres of canopy), as seen in Table 9.
Canopy and other land covers have
For the UTC assessment, the South Broadway
not changed since 2004, except for a
(or SoBro) District was designated as an “area
of interest” due to ongoing revitalization efforts, slight change in 2008 between lowlying vegetation and bare soil for a few
separate from any existing neighborhood
years, likely from a construction-related
boundary, and thus received a separate, basic
project.
canopy analysis.

Figure 10. SoBro Land Cover Map
(as seen from UTC Webviewer)

Tree canopy and related data were examined
to aid in the community’s ongoing efforts to
revitalize this 225-acre area between downtown
Louisville and the University of Louisville and
Churchill Downs. A land cover aerial map of
the area can be seen in Figure 10.

Table 9. SoBro Land Cover Changes
SO BRO

Year
2004

Year
2008

Year
2012

Rate of
Change

Tree Canopy

9%

9%

9%

0%

Buildings, Sidewalks, Roads, etc.
(“Impervious”)

80%

80%

80%

0%

Grass/Low-Lying Vegetation
("Other Pervious")

10%

8%

10%

0%

Bare Soil

0%

2%

0%

0%

Water

0%

0%

0%

0%
Canopy

Low Veg.

Impervious

22

FINAL DRAFT

Socioeconomics

Canopy & Socioeconomics
Are there correlations between Louisville
residents and their canopy cover? Analysis
of multiple socioeconomic factors and tree
canopy can provide answers, identify trends
and priority areas, and provide direction for
establishing planting goals.
Canopy coverage at the census tract and
council district levels (191 tracts, 26 districts)
was analyzed by socioeconomic and
demographic data collected from the U.S.
Census (2006-2010 American Community
Survey 5-Year Estimates). Highlights of
findings are listed below with data charts
available in Appendix B.

Socioeconomic Trends:
Canopy is higher in wealthier areas. Higher
income areas have as much as twice the
canopy coverage as lower income tracts.
Canopy decreases as population density
increases. The percentage of canopy
coverage decreases as population density
(number of people per square mile) increases.
Dense urban areas are made up of primarily
impervious surfaces, which leave little room
for large amounts of canopy.

Canopy is higher in areas with higher
percentages of older residents (ages 45
and older). Canopy was found to increase
as the percentage of the population over 45
increased, especially within the age group
45-64. When mapping the census tracts with
higher densities of this age group, these
groups tended to live in the outer areas of
Louisville, along with a smaller concentration
along the inner loop closer to the downtown
area.
Canopy tends to be lower in areas
dominated by rental properties, and
higher in areas with majority owneroccupied houses. Higher tree canopy is
strongly correlated with home ownership. This
relationship is likely attributed to a number
of factors: owner-occupied properties often
include greater amount of green space than
would typically be found in higher density
rental housing such as apartments and
townhomes. Homeowners also have more of
a financial investment in their properties and
neighborhoods, are less transient than renters,
and therefore are more likely to plant and care
for trees on their property and would desire
tree-lined streets.

Canopy is higher in areas with higher
educated residents. Canopy was found
to increase as the population with college
education increased, and canopy decreased
as the population with high school diplomas or
less increased.
Canopy is higher in areas dominated by
high-value homes. Canopy was found to
increase overall as the percentage of homes
valued over $100,000 increased, though the
increases are less pronounced with homes
valued at $100,000-$500,000 and more
pronounced with homes valued over $500,000.
As the percentage of homes valued under
$100,000 increases in an area, the canopy
decreases by almost half.
Canopy potential increases as the
concentration of newer homes increase.
Canopy was found to decrease in only those
structures built before 1950. Older structures
concentrated around the older city center of
Louisville are, in general, more urban with
less space for tree canopy. Newer homes built
after 1950 tended to be located in the outer
suburbs with more space for canopy.

23

FINAL DRAFT

CANOPY & THE
URBAN HEAT ISLAND
2015

Louisville Urban Tree
Canopy Assessment

As discussed in the Challenges section, Louisville has
directed efforts toward reducing its growing urban heat
island through tree canopy. Trees are considered one of
the most cost-effective, long-term solutions to mitigating
heat islands.
Heat reductions can be achieved by strategically locating
tree planting sites, but the first step is to identify hot
spots within Louisville.
Based on surface temperature data, it was determined
that 12% (approximately 31,000 acres) of Louisville is
heat-stressed, or classified as “hot spots” (over 94.5°F,
as explained further in the Two Methods to Identify Hot
Spots section on opposite page).
As expected, the vast majority of hot spots were areas
with large amounts of impervious surface and low
amounts of tree canopy. Tree canopy made up only 8% of
the land cover in designated hot spots, while impervious

and bare soil covered a combined 66%. The hot spots maps
(opposite page) clearly show a concentration within the urban
core of Louisville, from the downtown area to the airport.
Data (size, land cover, canopy) on hot spots have been made
available electronically at the census tract, council district,
neighborhood, suburban city, sewershed and parcel levels.
This data was also used in the prioritization of planting areas,
discussed in the Planting Plan Development section of this
report.

Louisville has 31,000 acres
(12% of study area) classified
as heat stressed, or “hot
spots.” Combined, hot spots
have 8% tree canopy and 66%
impervious and bare soil cover.

24

FINAL DRAFT
Heat Islands

Two Methods to Identify Hot Spots
UTC assessments can predict hot spots based on a ratio of impervious surfaces to tree canopy. Hot spot ratios in 100x100 meter grids are
graphically depicted in the Impervious to Canopy Ratio map (below left). However, Louisville has partnered with Georgia Institute of
Technology in a comprehensive study of Louisville’s heat island and potential mitigation efforts, (expected completion in summer 2015). This
study acquired actual surface temperature readings from Landsat 5 satellite imagery to identify actual hot spots - simultaneous temperature
readings allowing identification and segmentation of relatively hot areas. Readings were taking at one point in time on one cloudless summer
day in July 2010. Temperature findings ranged from 58°F - 125°F. For the purposes of this study, areas with the highest temperature range
(above 94.5°F) were designated as hot spots. These areas are shown in red in the Surface Temperature map (below right). Although both
methods were used in this assessment, this report utilizes results from the surface temperature data method.

Method 1: Impervious to Canopy Ratio

Method 2: Surface Temperature

25

FINAL DRAFT
Heat Islands

By Land Use
The hottest land use categories were found
to be commercial, multi-family residential,
and industrial. Half of all commercial land
was located in hot spot areas, along with
40% of multi-family residential land and
39% of industrial land. Together, these three
categories accounted for almost 20,000 acres
of heat stressed areas, or 63% of all hot spots
in Louisville, as shown in the Table 10.
Despite the fact that single-family residential
land use is the largest use of land in Louisville,

covering 34% (approximately 83,000 acres)
of the study area, it makes up only 13% (4,000
acres) of hot spot areas.
These numbers suggest that localized
urban heat island effect (defined as surface
temperature differential only, not as human
vulnerability) may not be significantly
abated by residential plantings alone. The
data do show that commercial districts
perform better when surrounded by trees
and landscaping (as mentioned in the Why
Trees section). Further analysis is required
to assess actual population vulnerability to

heat, especially at the neighborhood level, but
reducing temperature differentials countywide may be achieved in a shorter time by
accelerating tree planting in commercial and
multi-family areas.

Commercial, multifamily residential and
industrial land make
up 63% of all hot spots.

Table 10. Hot Spots by Land Use

Commercial
Industrial
Rights-of-way
Residential: Single Family
Public/Semi-Public
Residential: Multi-Family
Vacant
Parks/Open Space
Farmland
Totals

Size
(acres)
15,011
17,556
31,335
82,721
17,114
7,971
18,742
25,887
30,082
246,418

% Hot
Avg.
Hot Spot Spot in Temp (F) in
Acres Land Use Hot Spots
7,448
50%
94°
6,838
39%
92°
5,359
17%
90°
4,074
5%
88°
3,238
19%
89°
3,171
40%
93°
422
2%
84°
292
1%
83°
123
0%
83°
30,966
12%

Hot Spot Land Cover
Impervious /
Canopy
Veg.
Bare Soil
5%
17%
77%
2%
20%
77%
7%
25%
68%
18%
48%
34%
7%
26%
67%
12%
33%
54%
15%
44%
38%
13%
55%
31%
7%
57%
35%

26

FINAL DRAFT
Heat Islands

By Suburban City
Hot spots were identified in just over
half of the 83 suburban cities within
Louisville, totaling a combined area
of approximately 5,800 acres.
More than 40% of Watterson Park,
West Buechel, Forest Hills, Parkway
Village, and Hurstbourne Acres are
classified as hot spots.
Jeffersontown and St. Matthews
topped the list of large hot spot
acreage with 1,836 acres and 873
acres, respectively.
Table 11 lists the twenty suburban
cities with the largest hot spot areas.
Comprehensive hot spot data has
been made available electronically.

Table 11. Top 20 Suburban Cities with the Largest Amount of Hot Spots

Jeffersontown
St. Matthews
Shively
Middletown
Watterson Park
Lyndon
West Buechel
Hurstbourne
Heritage Creek
Douglass Hills
Forest Hills
Hurstbourne Acres
Graymoor/Devondale
Blue Ridge Manor
Windy Hills
Meadow Vale
Prospect
Parkway Village
Rolling Hills
Coldstream

Size
(acres)

Hot Spot
Acres

% Hot
Spots

6,372
2,771
2,953
3,264
919
2,317
412
1,146
292
845
175
211
472
117
567
117
2,514
56
121
141

1,836
873
776
479
432
344
174
152
114
96
89
83
78
35
30
25
25
24
24
14

29%
31%
26%
15%
47%
15%
42%
13%
39%
11%
51%
40%
17%
30%
5%
22%
1%
43%
20%
10%

Hot Spot Land Cover
Avg. Temp
(F) of Hot
Impervious
Canopy Veg.
Spots
/ Bare Soil
92°
93°
92°
89°
93°
90°
94°
91°
91°
91°
95°
94°
89°
93°
89°
91°
85°
94°
92°
91°

10%
10%
9%
8%
7%
9%
6%
11%
2%
16%
11%
15%
10%
13%
15%
0%
4%
12%
6%
6%

28%
19%
24%
26%
21%
26%
19%
23%
64%
28%
17%
26%
33%
21%
22%
6%
14%
32%
17%
56%

61%
71%
67%
65%
72%
65%
75%
66%
34%
55%
72%
60%
57%
66%
63%
93%
82%
55%
77%
38%

27

FINAL DRAFT
Heat Islands

By Council Districts
Comparing acreage of council district hot
spots (shown in Table 12), Districts 13,
21, and 4 produce the largest hot spots,
with a combined total of 8,100 acres or
26% of all Louisville hot spots. These
three districts have impervious and bare
soil land cover percentages in the 70’s.
Districts 4 and 6 in the old city boundary
report the largest percentage of the
district as hot spots.

Table 12. Council District Hot Spots
Council
District

Size
(acres)

District 13 20,928
District 21
7,143
District 4
4,153
District 6
3,291
District 10
6,410
District 11
7,032
District 15
4,316
District 3
4,537
District 18
7,406
District 24
6,972
District 22 12,991
District 2
4,986
District 20 39,330
District 17
8,916
District 26
4,160
District 12
8,402
District 19 19,935
District 23
7,988
District 1
9,389
District 9
6,515
District 5
5,371
District 16 16,158
District 8
4,322
District 7
7,956
District 25
7,702
District 14 18,013
Totals
254,322

Hot Spot
Acres
2,880
2,871
2,348
1,891
1,758
1,570
1,562
1,519
1,416
1,251
1,194
1,176
1,163
1,159
1,026
934
805
674
674
616
503
472
451
413
327
312
30,965

Hot Spot Land Cover
Hot Spots Avg. Temp
Impervious /
as % of
(F) of Hot
Canopy
Veg.
Bare Soil
District
Spots
3%
26%
70%
14%
86°
40%
4%
24%
73%
94°
57%
11%
17%
72%
92°
57%
10%
20%
70%
95°
9%
23%
69%
27%
91.6°
22%
12%
31%
57%
91°
36%
12%
25%
62%
91.6°
33%
9%
24%
67%
93°
19%
10%
25%
65%
91°
6%
27%
66%
18%
91°
9%
7%
47%
46%
88°
24%
7%
30%
63%
91.8°
3%
7%
42%
52%
84°
13%
5%
23%
72%
89°
25%
11%
22%
68%
92°
11%
5%
33%
61%
88°
4%
8%
27%
65%
86°
8%
8%
47%
45%
88°
7%
4%
29%
66%
87°
9%
10%
18%
72%
89°
13%
22%
66%
9%
86°
3%
6%
36%
58%
84°
10%
16%
22%
62%
90°
5%
9%
27%
64%
87°
4%
4%
28%
68%
86°
2%
3%
23%
71%
83°
12%

28

FINAL DRAFT
Heat Islands
When looking at the average temperatures
(shown in Figure 11), Districts 3, 4, 6, 21,
and 26 reported the highest temperatures
(above 92°F, highlighted in dark red in the
map). As a point of comparison, at the
exact same day and time, Districts 14, 16,
and 20 reported temperatures of 83-84°F.

Figure 11. Average Surface Temperature by Council District

The hottest districts are located in the
old city boundary as well as around
the industrial corridors and highways,
specifically along I-264, I-65 and Dixie
Highway / U.S. Highway 31W.

Hotter

Cooler

29

FINAL DRAFT
Heat Islands

By Neighborhoods
Comparing acreage of
neighborhood hot spots, Central
Business District, Algonquin, and
Fairgrounds each show more than
70% of their areas as heat stressed.
These neighborhoods have
impervious land cover around 80%
and tree canopy of 7% or less.
Table 13 shows the twenty
neighborhoods with the largest hot
spots. A full table of neighborhood
hot spot data has been delivered
electronically.

Table 13. Top 20 Neighborhoods with Largest Hot Spots

Central Bus.Dist.
Algonquin
Fairgrounds
Old Louisville
University
Park Hill
South Louisville
California
Phoenix Hill
Southside
Schnitzelburg
Saint Joseph
Wyandotte
Smoketown Jackson
Highland Park
Shelby Park
Standiford
Limerick
Highlands
Paristown Pointe

Size
(acres)

Hot Spot
Acres

% Hot
Spots

758
763
693
767
522
643
496
787
373
589
371
387
348
253
375
260
175
145
117
43

587
539
496
452
446
430
383
357
352
275
211
209
208
203
181
156
135
108
53
35

77%
71%
72%
59%
85%
67%
77%
45%
94%
47%
57%
54%
60%
80%
48%
60%
77%
74%
45%
81%

Hot Spot Land Cover
Avg. Temp
(F) of Hot
Impervious
Canopy Veg.
Spots
/ Bare Soil
97°
96°
97°
95°
97°
96°
96°
94°
98°
94°
94°
94°
94°
96°
94°
95°
97°
96°
94°
96°

7%
7%
4%
13%
8%
8%
12%
6%
10%
6%
17%
16%
22%
13%
4%
13%
2%
12%
17%
12%

9%
22%
17%
16%
21%
23%
23%
19%
17%
21%
32%
28%
32%
21%
41%
19%
33%
23%
19%
19%

84%
71%
79%
71%
71%
69%
65%
76%
73%
73%
52%
56%
47%
66%
55%
68%
65%
65%
64%
69%

30

FINAL DRAFT
Heat Islands

Figure 12. Average Surface Temperature by Neighborhood

Average temperature by neighborhood is
shown in Figure 12.
The hottest neighborhoods are clustered along
an interstate corridor from the urban center to
the airport.
Central Business District, Fairgrounds,
University, Phoenix Hill, and Standiford reported
the highest average temperatures of 97-98°F
(highlighted in dark red in the map). At the
exact same day and time, Cherokee Gardens,
Cherokee Seneca, and Iroquois Park reported
temperatures of 83-85°F.

Hotter

Cooler

FINAL DRAFT

31

CANOPY &
STORMWATER
2015

Louisville Urban Tree
Canopy Assessment

Louisville trees intercept an impressive
18.8 billion gallons of the 72.4 billion
gallons of stormwater runoff generated
each year.
Tree canopy is a proven and viable
solution to stormwater issues plaguing
many cities across the country, including
Louisville. Identifying priority locations
for stormwater management and
identifying canopy trends in those
locations are critical to mitigation efforts.
Metropolitan Sewer District’s (MSD)
stormwater system is located primarily
in the old city boundary of Louisville.
However, Louisville’s trees manage
stormwater across the study area. For this
reason, canopy was segmented by both
the urban sewersheds and across the
study area by council district to quantity
benefits and identify problem areas and
places for potential tree plantings as

green infrastructure solutions. This
data was also used in the prioritization
of planting areas, discussed in the
Planting Plan Development section of
this report.

By Council District
The amount of stormwater runoff per
council district is directly related to
the size of the district. Similarly, the
amount of runoff intercepted by tree
canopy is directly related to the acres of
existing tree canopy per district.
It can then be expected that the larger
outer districts (13, 14, 20) top the list of
highest value per acre of stormwater
management because of high UTCs
(as seen in Figure 13 and Table 14).
However one district close to the urban
core, District 8, makes the top five list
of highest benefits per acre despite its

smaller size, thanks to its 40% canopy coverage. Note
the effects of higher canopy cover percentages on
stormwater in Table 14.
Figure 13.
Stormwater
Value per Acre

32

FINAL DRAFT
Stormwater

Table 14. Stormwater by Council District

District 20
District 13
District 14
District 25
District 8
District 16
District 7
District 19
District 17
District 22
District 23
District 9
District 11
District 15
District 12
District 24
District 18
District 1
District 10
District 26
District 5
District 2
District 3
District 6
District 21
District 4
Totals

Stormwater Runoff Reduction by
Existing
Size
Canopy Canopy Impervious Impervious Volume Annually
(acres) (2012)
(2012)
(gal)
Acres
Acres
Canopy (gal)
39,330
51%
20,206
7%
2,568
11,197,418,696
4,028,965,127
20,928
48%
9,979
19%
3,990
5,958,397,841
1,989,815,876
18,013
46%
8,315
11%
1,970
5,128,512,247
1,657,891,089
7,702
45%
3,448
20%
1,559
2,192,723,572
687,575,820
4,322
40%
1,723
30%
1,283
1,230,585,045
343,591,415
16,158
40%
6,428
14%
2,203
4,600,265,859
1,281,678,562
7,956
40%
3,147
22%
1,782
2,265,023,946
627,496,537
19,935
39%
7,852
15%
2,948
5,675,679,060
1,565,567,728
8,916
36%
3,198
27%
2,404
2,538,383,141
637,595,194
12,991
35%
4,587
14%
1,819
3,698,664,701
914,587,930
7,988
34%
2,750
19%
1,491
2,274,254,121
548,372,021
6,515
33%
2,126
30%
1,952
1,854,782,621
423,924,892
7,032
32%
2,221
33%
2,328
2,002,151,351
442,786,238
4,316
31%
1,317
38%
1,656
1,228,764,872
262,545,484
8,402
29%
2,442
24%
2,035
2,392,204,192
486,976,715
6,972
29%
1,995
30%
2,072
1,984,912,216
397,738,078
7,406
27%
2,034
33%
2,443
2,108,415,234
405,529,520
9,389
27%
2,526
26%
2,462
2,673,004,083
503,665,733
6,410
25%
1,603
41%
2,659
1,825,069,630
319,642,574
4,160
24%
1,013
41%
1,708
1,184,351,961
202,009,584
5,371
23%
1,254
25%
1,350
1,529,076,719
249,976,802
4,986
22%
1,097
36%
1,777
1,419,618,463
218,645,662
4,537
21%
940
43%
1,959
1,291,615,984
187,362,341
3,291
18%
583
58%
1,903
936,920,358
116,207,196
7,143
16%
1,108
49%
3,497
2,033,646,152
220,879,597
4,153
12%
506
53%
2,210
1,182,243,632
100,820,560
254,322
72,406,685,697
18,821,848,275

Value of
Canopy
Value
Reduction per Acre
$13,456,744
$342
$6,645,985
$318
$5,537,356
$307
$2,296,503
$298
$1,147,595
$266
$4,280,806
$265
$2,095,838
$263
$5,228,996
$262
$2,129,568
$239
$3,054,724
$235
$1,831,563
$229
$1,415,909
$217
$1,478,906
$210
$876,902
$203
$1,626,502
$194
$1,328,445
$191
$1,354,469
$183
$1,682,244
$179
$1,067,606
$167
$674,712
$162
$834,923
$155
$730,277
$146
$625,790
$138
$388,132
$118
$737,738
$103
$336,741
$81
$62,864,974
$247

33

FINAL DRAFT
Stormwater

By Sewershed
MSD divides its stormwater system into 101
sewersheds, which are located in the urban
core of Louisville (see Figure 14).

Clifton neighborhoods. Canopy data on these
sewersheds can be seen in Table 15. A full-page
map showing the overlay of priority sewersheds
and neighborhood boundaries can be found in
Appendix B.

Based on stormwater data provided by MSD,
along with a list sewersheds with flooding and
drainage problems, canopy and other relevant
data was analyzed to identify trends and areas
of opportunity for green infrastructure efforts.

Overall, UTC has decreased in all ten priority
sewersheds since 2004, with losses ranging from
3% to 35%. Based on this trend, flooding and
drainage problems are not likely to improve
without additional canopy.

MSD’s priority sewersheds span across parts
of the Limerick, Smoketown Jackson, Shelby
Park, Germantown, Irish Hill, Phoenix Hill,
Highlands, Deer Park, Clifton Heights, and

UTC that intercept over 1 million gallons of
runoff for an annual benefit of $3,700. CSO
#153 has just 6 acres more UTC, but those
extra 6 acres result in the area being able to
intercept double the amount of runoff and
more than double the annual value to MSD.
These sewersheds have equal impervious
surface percentages, so tree canopy is a
significant factor in stormwater management
in these sewersheds.

This stormwater issue is one of the three
factors used to prioritize the planting plan,
The data suggests that even modest increases in
canopy cover in these priority sewersheds should discussed later in this report.
result in significant reductions in runoff volume
and treatment costs. CSO #154 has 35 acres of

Table 15. MSD Priority Sewersheds

CSO #141
CSO #82
CSO #120
CSO #154
CSO #153
CSO #106
CSO #137
CSO #83
CSO #119
CSO #179

Sewershed Data
Impervious
Annuals
MSD
Acres Surface % Stormwater
Priority
(2012)
Runoff (gal)
1
9
75%
2,498,591
2
13
37%
3,676,084
3
15
68%
4,391,465
4
35
47%
9,890,546
5
41
47%
11,723,744
6
10
29%
2,809,023
7
72
25%
20,545,401
8
30
58%
8,680,070
9
4
74%
1,271,412
10
223
64%
63,562,886
Totals:
453
129,049,222

Reduced by Canopy
Canopy Change Over Time
% of
Gallons
Value of Value / 2004
2008
2012
Rate of
CSO
Reduced
Reduction* Acre Canopy Canopy Canopy Change
Runoff
183,740
7%
$614
$70
11%
11%
10%
-3%
913,135
25%
$3,050
$236
37%
39%
35%
-5%
367,923
8%
$1,229
$80
16%
16%
12%
-24%
1,117,214
11%
$3,731
$107
18%
20%
16%
-8%
2,337,354
20%
$7,807
$190
31%
30%
28%
-8%
842,860
30%
$2,815
$285
66%
66%
43%
-35%
3,239,408
16%
$10,820
$150
27%
26%
23%
-16%
1,346,655
16%
$4,498
$148
25%
25%
22%
-11%
95,145
7%
$318
$71
12%
12%
11%
-13%
7,328,571
12%
$24,477
$110
17%
18%
16%
-4%
17,772,005 14%
$59,359
$131

* Based on the $3.34 determined by MSD as the cost to treat 1 gallon of runoff.

34

FINAL DRAFT
Stormwater
Figure 14. MSD
Sewershed
Locations

Table 16. Rates of Change in Canopy by Sewershed
HIGHEST Increase
in Canopy

Figure 15.
MSD Priority
Sewersheds

CSO #172
CSO #54
CSO #55
CSO #56
CSO #38
CSO #35
CSO #181
CSO #51
CSO #22
CSO #150

Size
(acres)

10
4
16
36
9
16
42
6
63
2

HIGHEST Decrease
Size
in Canopy
(acres)
CSO #27
9
CSO #106
10
CSO #58
121
CSO #16
4
CSO #126
37
CSO #120
15
CSO #187
6
CSO #104
69
CSO #148
26
CSO #121
102

Canopy Cover %
2004
2%
5%
2%
2%
2%
1%
2%
5%
3%
13%

2008
9%
11%
3%
3%
4%
3%
3%
6%
3%
15%

2012
8%
13%
5%
4%
4%
3%
4%
8%
4%
19%

Canopy Cover %
2004
2%
66%
10%
33%
59%
16%
19%
36%
54%
13%

2008
1%
66%
8%
35%
51%
16%
19%
32%
54%
10%

2012
1%
43%
7%
24%
44%
12%
15%
28%
42%
10%

Rate of
Change
247%
171%
161%
155%
136%
110%
77%
70%
57%
42%
Rate of
Change
-44%
-35%
-31%
-27%
-26%
-24%
-23%
-23%
-22%
-21%

Note: Canopy percentages have been rounded to nearest whole number. Rates of
change were calculated on the exact canopy number xx.xx%, then rounded to the
nearest whole number.

35

FINAL DRAFT

CANOPY &
ECOSYSTEM HEALTH
2015

Louisville Urban Tree
Canopy Assessment

The urban ecosystem is extremely complex
and diverse; existing in a multitude of layers
formed by small, functional ecosystems that
together form a larger system. The overall
health of the ecosystem depends on the
ability of the trees, plants, wildlife, insects, and
humans to interact. This crucial interaction
of species requires connected forests, or
greenspace corridors.
Urban development and sprawl not only
decrease canopy, but often carve up
connected forests into fragmented sections
(shown in Figure 16), prohibiting wildlife
interaction, and leading to further ecosystem
degradation. This, in turn, leads to a decline
in habitat quality and results in imbalance
to microclimates, an increased risk and
susceptibility to invasive species, and a loss of
regional air quality.

Figure 16. Wildlife corridors in area (A) link habitats while
fragmented forests in area (B) lead to a decline in habitat
quality. Image Source: Federal Interagency Stream Restoration
Group

36

FINAL DRAFT

Ecosystem Health

Louisville’s existing canopy was analyzed
for this fragmentation, focusing on
how and to what degree tree canopy is
spatially distributed and/or fragmented.
The findings are detailed at right.
In terms of forest health and ecosystem
integrity, a significant portion of
Louisville’s canopy is serving as a
functioning forested ecosystem (core
canopy). However, one fourth of the
canopy is severely fragmented.
Improvements can be made by creating
linkages between patches of forest.
Linking patch canopy areas through tree
planting to create more edge and core
areas will increase the recreational and
ecosystem benefits of natural woodlands
and greenways.

Forest Fragmentation Findings
Core Canopy (35,139 acres)
Tree canopy that exists within and relatively far from the forest/non-forest
boundary (i.e., forested areas surrounded by more forested areas). These
are the largest areas of contiguous canopy and function as native habitat.
This category makes up 37% of Louisville’s total canopy.

Edge Canopy (28,396 acres)
Tree canopy that defines the boundary between core forests and large
non-forested land cover features. When large enough, edge canopy may
appear to be unassociated with core forests. This category makes up 30%
of Louisville’s total canopy.

Patch Canopy (23,606 acres)
Tree canopy that comprises a small forested area that is surrounded by
non-forested land cover. This category makes up 25% of Louisville’s total
canopy.

Perforated Canopy (7,146 acres)
Tree canopy that defines the boundary between core forests and relatively
small clearings (perforations) within the forest landscape. This category
makes up 8% of Louisville’s total canopy.

37

FINAL DRAFT

Intersection of Breckinridge and Shelbyville Road. Trinity High School to lower left.
Image Source: Dr. Keith Mountain

CANOPY BENEFITS
Louisville Urban Tree Canopy Assessment

FINAL DRAFT

39
CANOPY
BENEFITS
2015

Louisville Urban Tree
Canopy Assessment

This study used a variety of tree canopy
assessment and analytical tools to quantify
and value the benefits of trees’ ability to store
carbon, clean the air, provide energy savings,
intercept and absorb stormwater and boost
property values. Detailed descriptions of
models used to calculate benefits listed in
Table 17 can be found in Appendix A.
The various ecosystem services derived from
Louisville’s canopy provide compelling data in
support of additional tree planting.
Benefits of Louisville trees have been
segmented by council district, census tract
and sewershed. Because these segmentations
vary so greatly in size, benefits were
compared using two metrics; first by the total
value of benefits, then by value of benefits per
acre.

Council district and census tract
highlights can be found on the following
pages. Full tables of benefits have been
provided electronically.

Louisville
trees provide
approximately
$330 million in
benefits annually.

40

FINAL DRAFT

Canopy Benefits

Overall Benefits
Overall, Louisville’s existing canopy provides
its residents with almost $330 million in
benefits annually.
On top of the annual benefits, carbon
stored over the lifetime of Louisville trees
contributes an additional $230 million in
benefits, bringing the collective benefit
amount to $560 million.
Table 17 lists a summary of the benefits
provided by Louisville trees. Specifics on
each of these benefits are detailed in the
following pages.

Table 17. Louisville Tree Canopy Benefits
Benefit

Quantity

Unit

STORMWATER: Reduction of Runoff 18,835,266,390 gallons

Value
$62,909,790

ENERGY: Savings from Avoided Cooling

67,649,325

kWhs

PROPERTY: Increases in Property Values

-

$

AIR: Carbon Monoxide (CO) Removed

149,120

lbs.

$99,078

AIR: Nitrogen Dioxide (NO2) Removed

517,780

lbs.

$219,678

4,366,940

lbs.

$7,932,540

622,280

lbs.

$78,727

1,242,280

lbs.

$3,879,821

444,112

tons

$8,599,490

AIR: Ozone (O3) Removed
AIR: Sulfur Dioxide (SO2) Removed
AIR: Dust, Soot, Other Particles Removed
(Particulate Matter, PM10)
Carbon Sequestered

$5,463,356
$239,969,791

Total Annual Benefits $329,152,271
Carbon Storage Over Canopy's Lifetime
(not an annual benefit)

11,941,333

tons

$231,224,066

Total Benefits Overall $560,376,337

41

FINAL DRAFT

Canopy Benefits

18.8 billion gallons
of stormwater
intercepted annually

Stormwater Runoff Reduction
Trees in Louisville are able to intercept an
impressive 18.8 billion gallons of stormwater
annually – that’s enough to fill over 28,000
olympic-sized swimming pools. This important
infrastructure service provided by trees is
valued at approximately $63 million. Trees
intercept rainfall by temporarily holding
rainwater on leaves and bark, delaying
that water from reaching the ground and
moderating peak runoff quantities. Tree
roots also directly absorb stormwater by
consuming water stored in soil pores, and
thereby increasing the capacity of local soils
to store rainwater. Stormwater reduction rates
are based on an average annual rainfall of 45.2
inches and equates to almost 200,000 gallons
of stormwater reduction per acre of tree
canopy.

$5 million in energy
savings for consumers
annually

$240 million increase
in Louisville property
values

Energy Savings
The cooling benefit of shade trees is perhaps
the most widely recognized benefit of trees.
The urban forest in Louisville is estimated to
save 67 million kilowatt hours of energy - a
savings of over $5 million for consumers.
Natural cooling provided by urban trees
reduces consumer demand for electricity
which, in turn, also reduces harmful emissions
released from the burning of fossil fuels
because of the decreased demand on power
plants. The cooling benefit of shade trees
can also be felt at the street level where lower
ambient temperatures of 5 to 15 degrees have
been recorded around street trees (Miller,
1997). Adding trees for their cooling benefits
alone in areas with large amounts of concrete
(impervious surfaces) would quickly help
reduce ambient temperatures in Louisville’s
urban heat islands.

Increases in Property Values
How many times have realtors enticed
prospective buyers to a community touting
the “highly sought-after neighborhood with
tree-lined streets?” In one survey by Arbor
National Mortgage and American Forests,
83% of realtors indicated that large, mature
trees had a “strong or moderate impact” on
home sales under $150,000. For homes over
$250,000, the response increases to 98%.
Homes with trees were also reported to sell
more quickly that those without. Louisville
trees can be attributed almost $240 million
in property value increases, representing the
largest single benefit value reported.

42

FINAL DRAFT

Canopy Benefits

6.9 million lbs. of
pollutants removed
from the air annually

Air Quality Improvements
Every year Louisville trees remove huge
amounts of pollution from the air: over 150,000
lbs. of carbon monoxide (CO), 500,000 lbs.
of nitrogen dioxide (NO2), 4.3 million lbs.
of ozone (O3), 600,000 lbs. of sulfur dioxide
(SO2) and 1.2 million lbs. of dust , soot and
other “particulate matter” (PM10). This
equates to an impressive value of $12.2
million worth of air quality improvements
annually. Ozone pollution represents the
greatest benefit value to Louisville residents
at $7.9 million. Reforestation efforts in and
around urban areas have been shown as
one of the more cost effective and feasible
methods to controlling dangerous groundlevel ozone, which is known to cause increases
in respiratory and cardiovascular diseases
and human deaths world-wide (Kroeger et al,
2014).

400,000 tons of carbon
dioxide removed from
the atmosphere annually

Carbon Reduction
The total carbon reduction benefit provided
by trees can be measured in two categories.
The first is the amount of carbon dioxide
absorbed by tree leaves annually, which has
been calculated at over 400,000 tons. The
second is the amount of carbon stored in
woody tissue of living trees over its lifetime,
calculated at almost 12 million tons. These
two carbon sequestration avenues represent
a total benefit value of $240 million. This is an
important benefit to Louisville residents as it
mitigates atypical climatic patterns believed
to be influenced by excess atmospheric
carbon.

43

FINAL DRAFT

Canopy Benefits

By Council District
Tree benefits by council district were
examined in two ways: total benefits value
and benefits per acre. Benefits per acre
allow a more equal comparison of benefits
contributions.

Table 18 lists this information for each council
district, and maps of both metrics can be seen
in Figures 17 and 18.
The five council districts with the highest
dollar value of benefits (Districts 20, 13,
19, 14 and 16) are all situated on the outer

Figure 17. Total Benefits, by Council District

perimeter of the study area, cover 45% of the
study area, and represent 53% ($296 million)
of Louisville’s total canopy benefits. This can
be attributed to their large size and less dense
population.

Figure 18. Benefits per Acre, by Council District

FINAL DRAFT

44

Canopy Benefits

The five council districts with the smallest dollar
value of benefits (Districts 2, 3, 4, 6 and 26) make
up 8% of the entire study area, are located in and
around the old city boundary and contribute 5%
($28 million) of Louisville’s total benefits.

Districts 25 ($1,735) and 7 ($1,692 per acre),
downtown and the airport, showed the
located closer to the urban center, emerged as lowest benefits per acre.
having the highest benefits per acre. Districts
4 ($436 per acre) and 21 ($653 per acre),
situated along the urban corridor between

Table 18. Canopy Benefits by Council District, by Value per Acre
District 25
District 7
District 8
District 20
District 17
District 16
District 13
District 19
District 23
District 14
District 11
District 9
District 22
District 18
District 24
District 26
District 15
District 12
District 10
District 3
District 2
District 1
District 5
District 6
District 21
District 4

Total
Acres
Canopy Air Quality
Carbon*
Stormwater Energy Saved Property Value
7,702
45%
$444,206
$8,760,968
$2,296,503
$210,728
$10,096,286
7,956
40%
$403,309
$7,998,980
$2,095,838
$250,340
$10,427,460
4,322
40%
$221,737
$4,387,246
$1,147,595
$329,573
$5,043,212
39,330
51%
$2,591,117 $51,512,548
$13,456,744
$253,934
$43,342,162
8,916
36%
$403,954
$8,110,591
$2,129,568
$182,557
$10,847,858
16,158
40%
$820,560
$16,259,169
$4,280,806
$221,731
$18,441,492
20,928
48%
$1,293,914 $25,203,540
$6,645,985
$240,113
$21,243,585
19,935
39%
$1,024,610 $19,873,390
$5,228,996
$243,783
$20,208,063
7,988
34%
$359,841
$7,016,668
$1,831,563
$176,974
$7,948,402
18,013
46%
$1,078,055 $21,097,071
$5,537,356
$212,001
$15,959,913
7,032
32%
$292,429
$5,617,890
$1,478,906
$177,075
$7,040,259
6,515
33%
$270,698
$5,398,043
$1,415,909
$321,471
$6,255,606
12,991
35%
$590,877
$11,567,060
$3,054,724
$148,793
$11,694,229
7,406
27%
$258,333
$5,158,625
$1,354,469
$200,204
$6,866,253
6,972
29%
$257,499
$5,054,704
$1,328,445
$182,321
$5,873,061
4,160
24%
$132,494
$2,580,368
$674,712
$179,111
$3,491,620
4,316
31%
$175,562
$3,333,192
$876,902
$215,647
$3,008,409
8,402
29%
$319,516
$6,202,656
$1,626,502
$169,222
$6,090,942
6,410
25%
$210,671
$4,066,686
$1,067,606
$227,676
$4,500,380
4,537
21%
$122,539
$2,398,355
$625,790
$186,699
$3,198,419
4,986
22%
$141,793
$2,783,658
$730,277
$154,054
$3,419,855
9,389
27%
$326,764
$6,414,243
$1,682,244
$179,951
$5,469,811
5,371
23%
$164,108
$3,189,652
$834,923
$258,433
$2,983,410
3,291
18%
$74,639
$1,484,569
$388,132
$211,952
$1,732,600
7,143
16%
$144,293
$2,788,586
$737,738
$189,599
$3,491,474
4,153
12%
$65,144
$1,290,270
$336,741
$139,414
$1,221,920
* Total carbon includes annual benefits plus lifetime storage benefits. All other values are annual.

TOTAL
$21,808,692
$21,175,927
$11,129,363
$111,156,504
$21,674,528
$40,023,759
$54,627,137
$46,578,842
$17,333,448
$43,884,397
$14,606,559
$13,661,728
$27,055,683
$13,837,883
$12,696,030
$7,058,304
$7,609,712
$14,408,839
$10,073,019
$6,531,802
$7,229,637
$14,073,012
$7,430,525
$3,891,892
$7,351,690
$3,053,488

Value / Acre
$1,735
$1,692
$1,596
$1,563
$1,554
$1,507
$1,449
$1,375
$1,323
$1,307
$1,307
$1,298
$1,224
$1,197
$1,122
$1,099
$1,019
$1,003
$960
$930
$912
$840
$811
$748
$653
$436

45

FINAL DRAFT

Canopy Benefits

By Census Tract
Tree benefits segmented by the 191 census
tracts were examined by both the total
benefits value and benefits value per acre (as
described in the previous Benefits by Council
Districts section).

Table 19 lists the highest and lowest five tracts
for both metrics, and maps of both metrics can
be seen in Figures 19 and 20.
The five census tracts with the highest dollar
value of benefits are all situated on the outer
perimeter of the study area, cover 22% of the

Figure 19. Total Benefits, by Census Tract

entire county and provide 31% ($176 million)
of the total tree benefits value. The lowest five
census tracts on that list make up less than 1%
of the entire study area and provide less than
1% (approximately $1.1 million) of the total
tree benefits.

Figure 20. Benefits per Acre, by Census Tract

FINAL DRAFT

46

Canopy Benefits

Table 19. Five Highest and Lowest Tracts for Benefits (Total and Per Acre)
Highest Total Benefits
Tract
116.04
120.03
116.01
116.03
103.07

Acres
18,778
11,749
10,687
8,811
5,863
Totals

Canopy
57%
76%
49%
51%
44%

Air Quality Total Carbon
$1,402,267
$28,123,360
$1,161,598
$23,548,740
$671,068
$13,604,480
$584,985
$11,859,060
$340,559
$6,829,560
$4,160,477 $83,965,200

Stormwater
$7,139,228
$5,981,554
$3,452,253
$3,005,324
$1,736,555
$21,314,914

Energy Saved Property Value
$53,953
$22,429,415
$62,925
$16,744,194
$54,057
$11,361,923
$43,878
$7,965,310
$28,734
$7,456,881
$243,547
$65,957,723

TOTAL
BENEFITS
$59,148,224
$47,499,012
$29,143,781
$23,458,558
$16,392,289
$175,641,864

Value / Acre
$3,150
$4,043
$2,727
$2,662
$2,796

Energy Saved Property Value
$7,303
$41,073
$5,273
$76,962
$11,539
$80,966
$12,154
$105,722
$6,084
$85,817
$42,353
$390,540

TOTAL
BENEFITS
$115,932
$205,762
$272,135
$222,786
$321,711
$1,138,327

Value / Acre
$613
$1,244
$1,613
$513
$1,809

Lowest Total Benefits
Tract
50
35
53
37
49

Acres
189
165
169
434
178

Canopy
11%
8%
13%
18%
5%

Air Quality Total Carbon
$2,555
$51,800
$4,679
$94,860
$6,823
$138,160
$4,011
$80,400
$8,675
$175,840
$26,743
$541,060

Stormwater
$13,201
$23,988
$34,647
$20,499
$45,295
$137,630

Highest Benefits per Acre
Tract
84
114.05
120.03
120.01
122.04

Acres
205
611
11,749
4,444
1,779

Canopy
23%
2150%
7645%
6725%
5628%

Air Quality Total Carbon
$6,109
$1,204,000
$17,181
$3,370,460
$1,161,598 $23,548,740
$389,174
$7,889,780
$129,398
$2,622,960

Stormwater
$31,538
$87,497
$5,981,554
$1,990,061
$666,798

Energy Saved Property Value Total Benefits
$22,505
$183,312
$1,447,463
$34,554
$526,453
$4,036,145
$62,925
$16,744,194
$47,499,011
$38,058
$5,977,214
$16,284,287
$49,753
$2,918,738
$6,387,647

VALUE /
ACRE
$7,060
$6,603
$4,043
$3,665
$3,590

Air Quality Total Carbon
$2,555
$51,800
$17,127
$347,100
$4,679
$94,860
$33,420
$677,720
$8,675
$175,840

Stormwater
$13,201
$86,109
$23,988
$177,731
$45,295

Energy Saved Property Value Total Benefits
$7,303
$41,073
$115,933
$3,175
$290,909
$744,421
$5,273
$76,962
$205,763
$1,975
$268,913
$1,159,760
$6,084
$85,817
$321,711

VALUE /
ACRE
$652
$562
$474
$264
$252

Highest Benefits per Acre
Lowest Benefits per Acre
Tract
50
91.03
35
9801
49

Acres
178
1,324
434
4,396
1,275

Canopy
11%
10%
8%
6%
5%

* Total carbon includes annual benefits plus lifetime storage benefits. All other values are annual.

47

Louisville suburb south of Bowman Field
Image Source: Dr. Keith Mountain

FINAL DRAFT

ACTION PLAN
DEVELOPMENT
Louisville Urban Tree Canopy Assessment

FINAL DRAFT

49
Action Plan
Development
2015

Louisville Urban Tree
Canopy Assessment

Clearly trees provide many benefits
in Louisville, and this UTC assessment
revealed that there are many opportunities
for canopy expansion to increase these
benefits. Tree planting, however, should be
guided by realistic goals and a prioritized
plan based on local issues and values.

Setting Goals
Setting tree canopy and planting goals
is an important step in the planning
process as it provides metrics to measure
performance throughout the coming years
and ensures the goals set are realistic.
What canopy percent to aim for?
American Forests, a recognized leader
in conservation and community forestry,
has established standards and goals for

canopy cover in metropolitan areas. They
recommend that cities set an overall
canopy goal of 40% with 15% canopy in
central business districts, 25% canopy
in urban neighborhoods, and 50%
canopy in suburban neighborhoods.
When compared to American Forest’s

canopy standards, the data indicates that
Louisville’s overall and urban residential
canopy meets or exceeds the targets.
However, the UTC in both the central
business district and suburban residential
areas fall significantly short of the
recommended goals (see Table 20).

Table 20. Canopy Standards

Average of All Zones
Central Bus. Districts
Urban Residential**
Suburban Residential**

American
Forest Rec.*
40%
15%
25%
50%

Louisville Canopy
2004
2008
2012
40%
38%
37%
7%
7%
8%
29%
28%
26%
37%
36%
35%

*American Forests recommendations for metropolitan areas east of the Mississippi.
** For purposes of this snapshot analysis, council districts 4,5,6,8 and 9 were considered
urban residential areas, and council districts 12,16,17, 23 and 24 were considered suburban
residential.

2012 URBAN
CD4

Acres Canopy Acres
4,153
506

SUBURBAN
CD12

Acres
8,402

Future Canopy Including Ash Loss
2012 Canopy
37%

37%

Plan Goals

Louisville Future
Figure 21. Louisville’s Estimated Future Canopy
Canopy Estimates

However, every community is unique, and
the American Forest goals should only be
considered general guidelines. Determining
tree canopy goals for Louisville will involve
a multi-step process of using these “ideal”
canopy rates in combination with what is
realistic and acceptable in Louisville, when
balanced with other community, economic and
social goals.

Future Canopy Based on Existing Trends

50%

Future Canopy Including Ash Loss

45%

40%

38%

40%

37%

35%
32%

35%

28%

30%

25%

31%
25%

28%
24%

20%

21%

This esimation of trees is based on a 29’ average canopy diameter of a mature tree.

Year

2052

2042

2032

2022

2012

15%
2008

If current trends hold,
Louisville canopy is
projected to decrease
to 31-35% in the next
ten years, dropping to
as low as 21% over the
next forty years.

Actual Canopy

Canopy

What does the future look like? Louisville
lost over 6,500 acres of tree canopy between
2004 and 2012. This effectively represents an
average annual loss of 820 acres, equivalent
to more than 54,000 trees per year.1 If this
current trend holds, and compounds with the
losses projected from EAB, Louisville tree
canopy is projected to fall to 31%-34% in the
next ten years, dropping to as low as 21% over
the next forty years (see Figure 21).

1

37%

31%

FINAL DRAFT

2004

50

37%
37%

28%

37

51

FINAL DRAFT
Plan Goals

How much canopy is possible in Louisville?
The level of possible canopy is determined by adding
the existing canopy to the amount of available planting
space in Louisville. This data is important to have when
setting realistic canopy goals.
Analysis of available planting space involves more than
simply assuming all pervious surfaces currently without
trees (grass/low-lying vegetation or bare soil) are
potential planting locations. Some pervious surfaces
are not suitable for planting (golf courses, agricultural
fields, cemeteries, airports, recreational fields, some
parts of rights-of-way, etc.). Likewise, not all impervious
areas should be ruled out for planting, as trees can still
be added in certain locations (trees in sidewalk areas,
parking lot islands, etc.).
Potential realistic plantable areas are therefore
determined by excluding those pervious areas
unsuitable for planting and including impervious areas
where trees could realistically be added. The resulting
area is termed Realistic Plantable Areas (RPAs).
The maximum canopy possible is, therefore,
determined by calculating the resulting canopy if
100% of RPAs were indeed planted with the largest
canopy-producing tree possible for that location. That
canopy can then be added to the existing canopy to
reach a maximum canopy percentage. UTC analysis
has indentified over 66,000 acres of RPAs (land that
could be planted with trees). Planting 100% of the

Table 21. Potential Canopy by Council District

District 1
District 2
District 3
District 4
District 5
District 6
District 7
District 8
District 9
District 10
District 11
District 12
District 13
District 14
District 15
District 16
District 17
District 18
District 19
District 20
District 21
District 22
District 23
District 24
District 25
District 26
Totals

2012
Canopy
27%
22%
21%
12%
23%
18%
40%
40%
33%
25%
32%
29%
48%
46%
31%
40%
36%
27%
39%
51%
16%
35%
34%
29%
45%
24%
37%

Maximum
Realistic
Potential Canopy Possible
Plantable Areas Canopy of
(current canopy +
potential canopy)
(RPAs) (acres)
RPAs
2,343
25%
52%
1,587
32%
54%
1,498
33%
54%
678
16%
29%
1,047
19%
43%
729
22%
40%
1,946
24%
64%
961
22%
62%
1,313
20%
53%
1,730
27%
52%
2,019
29%
60%
2,694
32%
61%
5,417
26%
74%
4,016
22%
68%
1,088
25%
56%
3,787
23%
63%
2,759
31%
67%
2,095
28%
56%
5,126
26%
65%
7,962
20%
72%
1,757
25%
40%
4,367
34%
69%
3,047
38%
73%
2,514
36%
65%
2,340
30%
75%
1,216
29%
54%
66,037 acres total
27%
63%

52

FINAL DRAFT

Plan Scenarios

RPA sites would add 26% canopy cover to the existing 37%
canopy, setting the maximum UTC possible in Louisville to be
63%. Table 21 shows the maximum canopy levels for each of
Louisville’s council districts.
What should be the canopy goals for Louisville? Now
that past loss trends and maximum possible canopy have
been identified, realistic canopy goals can be developed. A
good starting point is the combination of American Forests
recommended canopy, Louisville’s preliminary goals (no net
loss, 40% and 45% canopy), and maximum canopy possible.
A determination of goals must be made locally, based on what
is economically, ecologically, and politically feasible for canopy
across various land uses and jurisdictions. This will require
input and support from the public, local leaders, and subject
matter experts to set local goals that are based on local values,
local environmental and quality of life goals, compliance with
federal and local clean air and water regulations, and economic
development plans.
Once realistic goals are determined, the Louisville Metro
Government and stakeholders can pursue those goals using
policies, procedures, education, incentives, and various funding
avenues.

Factoring in Ash Loss
EAB is a significant urban threat in Louisville and tree loss due to this
exotic insect should be factored into the discussion future canopy loss.
However, this UTC assessment does not reflect tree losses attributable
to EAB infestations because it was only during the last few years that
the EAB populations reached a critical mass and had infested trees
long enough for symptoms to occur. However, it is likely that 2015
aerial photography will show measurable losses in canopy due to EAB.
It is estimated that between 10% and 17% of Louisville’s tree canopy is
comprised of ash species (UK 2014), equating to an estimated 625,000
- 1,000,000 trees that will be lost to EAB in the next five to ten years.
Further analysis may be required to fine-tune the actual number of
trees that will be lost to EAB in the coming years. Using more recent
aerial photography in combination with an i-Tree Eco or hyperspectral
imagery project will identify the location of the ash tree populations
and concentrations in Louisville.
If analysis reveals that ash are primarily in naturalized woodland areas,
annual tree replacement numbers can be reduced. Existing younger
understory trees will grow and other mature trees’ crowns will spread
to fill the gaps left by ash trees. Targeted reforestation may be the only
tree planting response required in these areas to offset the impact of
EAB.
However, if a significant number of ash trees are in urban and suburban
areas growing as landscape trees, then tree replacement planting on
at least a one-to-one ratio or greater should be considered, as ash in
these locations would be contributing significant stormwater, urban
heat island, and energy conservation benefits.

FINAL DRAFT

53

Plan Scenarios

Action Scenarios

The following scenarios are offered for
perspective and as a reference for the
recommendations presented later in this report.

Given the serious loss of regional tree
canopy, an aggressive plan must be
devised and implemented to achieve
Louisville’s preliminary goals of no net
loss in five years and 40% or 45% overall
canopy in future years.

Each scenario involves a defined intensive set
of actions (or lack thereof) over the first ten
years, then less intense but ongoing action
in the following thirty years to reach predetermined goals in a forty-year time span.

Note that increases in tree canopy can come
not only from planting new trees, but also from
preserving existing trees. For this reason,
each scenario includes an option for planting
efforts alone, as well as a combination of
planting and loss reduction. The scenarios
show that reducing the rate of annual canopy
loss can reduce planting costs by as much
as 50%. Specific loss reduction efforts

Table 22. Scenarios for Future Canopy
Scenario 0:
No Action

Scenario 1: No Net Loss

Scenario 2: 40% Canopy Goal Scenario 3: 45% Canopy Goal

1a

1b

2a

2b

3a

3b

No
Action

Planting
Only

Planting + Loss
Reduction

Planting
Only

Planting + Loss
Reduction

Planting
Only

Planting + Loss
Reduction

Trees Planted Annually, Years 1-10

0

54,120

27,060

102,432

75,372

186,384

159,324

Trees Planted Annually, Years 11-40

0

54,120

27,060

54,120

27,060

54,120

27,060

32,800

32,800

16,400

32,800

16,400

32,800

16,400

Acres Planted Over 40 years

0

32,800

16,400

40,120

23,720

52,840

36,440

Trees Planted Over 40 years

0

2,164,800

1,082,400

2,647,920

1,565,520

3,487,440

2,405,040

Resulting Canopy at Year 40

24%

37%

37%

40%

40%

45%

45%

$0

$1,039,104,000

$519,552,000

$1,271,001,600

$751,449,600

Method

Acres Lost Over 40 years

Total Planting Costs

$1,673,971,200 $1,154,419,200

Assumptions and Notes on Scenarios:
All tree plantings are landscape trees (2” caliper or higher) valued at $480 per tree retail value (tree plus labor)
Tree counts are based on a 29’ average crown diameter of a mature tree, one acre of land can hold 66 trees.
Scenarios extend 40 years to allow for trees planted in first ten years to mature.
Scenarios do not factor in ash loss from EAB (see Factoring in Ash Loss inset).
To demonstrate the impact of loss reduction efforts, annual loss was reduced in 1b, 2b and 3b by 50% as an example only.
Full tables on calculations to reach these numbers can be found in Appendix B.

54

FINAL DRAFT

Plan Scenarios

(policies, ordinances) are presented in the
recommendations section. Each scenario is
summarized in Table 22, with a detailed table
in Appendix B.
Scenario 0: No Action
A “no action” scenario is provided as a
baseline. If no changes are made and zero
trees are planted, overall canopy will drop to
24% by year 40 (closer to 20% with the impact
of EAB).
Scenario 1: No Net Loss
Assuming no change in rate of annual canopy
loss, Louisville will need to add just over 820
acres (or approximately 54,000 trees) every
year to counter the annual historic decline.
As shown in scenario 1a, forty years of
working to counter losses by tree planting
alone will require planting of just over 2.1
million trees, equivalent to over $1 billion
dollars.
Scenario 1b assumes loss reduction efforts are
in place that cut the current annual loss rate
in half (to only 410 acres lost per year). With
this in place, no net loss could be achieved
by planting just over 27,000 trees every year.
After forty years, this equates to 1 million
trees planted, equivalent to $520 million –
approximately half the cost of scenario 1a.

Defining “No Net Loss”
It is important to consider that there are two ways to define “no net loss” in urban tree
canopy, and the differences are worth noting from the outset.
Method #1: Replant One Tree for Every Tree Lost
A one-to-one ratio of the trees lost to trees planted is a valid way to define “no net loss.”
This is based on a long-term perspective that accepts the premise that a new young tree
will replace a lost mature tree over time.
Method #2: Replace Actual Square Footage of Canopy Lost
Another valid way to define“no net loss” is to calculate crown acreage of mature trees lost
and balance that immediately with the acreage of new tree crowns planted. This view is
based on a more short-term perspective of planting multiple new trees for every mature
tree lost in an effort to immediately restore actual canopy area lost.
For example, when a mature oak with a canopy of 3,000 square feet is lost, achieving no
net loss from planting a two-inch tree with a 300 square foot canopy could be achieved
in two ways, depending on your viewpoint. Under Method #1, planting one new tree to
replace the mature oak achieves no net loss. Under Method #2, ten trees must be planted
to achieve no net loss.
In practice, both definitions can be used in a large region like Louisville. For rural and
woodland areas, the one-to-one ratio is typically used by traditional forest managers given
trees’ life spans and other characteristics of the ecosystem. In urban areas, urban forest
managers tend to want equal square footage of canopy replaced due to the lack of natural
environment and the immediate benefits even small crowns can provide the community,
especially for stormwater management.
The choice of definition (often the basis of future tree planting projects, land use policies,
regulations, and educational efforts) is a local decision, based on local community values.

55

FINAL DRAFT

Plan Scenarios

Scenario 2: 40% Canopy Goal
This study has determined Louisville will need
to add approximately 7,300 acres of canopy
to the existing canopy to reach the 40% UTC
goal. At the current rate of annual loss, this
will be a challenging task.
Scenario 2a assumes the ongoing rate of
canopy loss (820 acres or 54,000 trees a year)
throughout the 40-year period, but with heavy
planting levels (100,000 trees per year) over
the first ten years to both counter the annual
loss and add the 7,300 acres needed to reach
the 40% UTC goal. After the first ten years of
heavy planting, work in the remaining 30 years
would just involve planting to offset standard
annual losses (820 acres per year). Forty years
of working to achieve 40% canopy by tree
planting alone will require just over 2.6 million
trees planted, equivalent to over $1.3 billion
dollars.
Scenario 2b assumes losses are reduced by
half and active tree planting over the first ten
years. In the first ten years, only 75,000 new
tree plantings would need to be planted, with
27,000 needed for the next 30 years to reach
the 40% canopy cover goal. This equates
to a total of 1.5 million trees planted for
approximately $750 million – again, just over
half the cost of scenario 2a that is dependent
on tree planting alone to reach goals.

Scenario 3: 45% Canopy Goal
According to the 2012 findings in this report,
Louisville will need to add approximately
20,000 acres to reach the 45% UTC goal. This
will be a challenging goal to reach by planting
alone. For this reason, tree preservation
efforts become even more critical for overall
success.
Scenario 3a assumes the continued loss of
canopy of over 820 acres (54,000 trees) a year
throughout the 40-year period, but with heavy
planting levels (186,000 trees per year) over
the first ten years to both counter the annual
loss and add the 20,00 acres needed to reach
the 45% UTC goal. After the first ten years
of heavy planting, work in the remaining 30
years would again involve planting only to
offset annual losses (820 acres per year). Forty
years of working to achieve the 45% canopy
goal through tree planting alone will add up to
almost 3.5 million trees planted, equivalent to
over $1.6 billion dollars.
Scenario 3b assumes substantial tree planting
over the first ten years, but with canopy loss
slowed to half the current rate. In the first ten
years, only 160,000 new tree plantings would
need to be planted, with 27,000 needed for the
next 30 years to reach the 45% canopy cover
goal. This equates to a total of 2.4 million
trees planted for approximately $1.1 billion –

30% less than the cost of depending on tree
planting alone in scenario 3a.
Clearly, tree preservation efforts to arrest the
current annual loss rate are just as important
to incorporate into urban forest management
as tree planting. Recommendations for tree
preservation initiatives are included in the
recommendations section of this report.

56

FINAL DRAFT

Plan Scenarios

Planting Plan Format
The UTC-based and prioritized
planting plan provided within this
project is a tool that can be used
for planning, budgeting, applying
for grants, inter-agency project
development, public education, and
many other uses.
The plan should not, however, be
considered as a traditional landscape
design and installation plan. It exists
as an electronic GIS data layer with
embedded information (Figure 22),
and as such can be easily queried,
updated, and used for additional
project-based analyses. Tree planting
areas have not been field-verified
and the tree quantities suggested for
a given area are estimates based on
the accuracy of the data provided by
LOJIC and other project partners.

Figure 22. GIS Screen Shot

57

FINAL DRAFT

Plan Prioritization



environmental features/sensitivity (a
combination of canopy location related to
surface waters and impaired waterways,
soil type, floodplains, slope, and forest
fragmentation),



stormwater issues, and



urban heat island concentrations.

Each factor was used to create individual
grids that were assigned a value between 0
and 4 identifying priority planting importance
from Very Low to Very High. The resulting
information was then mapped for individual
categories of information, such as urban

Very Low
Low

UHIIsland Priority
Urban Heat
UHI
UHI Number of
Priority
Areas of
Number
Number of
Priority
Very
Low
277,044
Priority
Areas
Areas
Low
120,293
Very Low
277,044
Very
Low
277,044
Moderate
12,178
Low
120,293
Low
120,293
High
107,161
Moderate
12,178
Moderate
12,178
Very
High
57,548
High
107,161
High
107,161
Very High
57,548
Very High
57,548

Priority
Level

Acres
Acres
3,534
Acres
25,479
3,534
3,534
11,411
25,479
25,479
16,634
11,411
11,411
8,678
16,634
16,634
8,678
8,678

Stormwater Management Priority
STORMWATER
STORMWATER
STORMWATER Number of
Priority
Acres
Areas of
Number
Number of
Priority
Acres
Very
Low
272,215
2,238
Priority
Acres
Areas
Areas
Low
73,140
3,606
Very Low
272,215
2,238
Very Low
272,215
2,238
Moderate
67,148
26,493
Low
73,140
3,606
Low
73,140
3,606
High
107,384
25,939
Moderate
67,148
26,493
Moderate
67,148
26,493
Very High
54,337
7,461
107,384
25,939
High
107,384
25,939
Very High
54,337
7,461
Very High
54,337
7,461

Moderate

To identify planting areas that will return
the greatest and most diverse amount of
benefits to Louisville, each plantable area was
evaluated based on three factors:

ENVIRONMENTAL
Environmental
Sensitivities Priority
ENVIRONMENTAL
ENVIRONMENTAL
Number of
Priority
Acres
Areas of
Number
Number
of
Priority
Acres
Very
Low
363,529
38,752
Priority
Acres
Areas
Areas
Low
42,453
5,633
Very Low
363,529
38,752
Very Low
363,529
38,752
Moderate
57,813
7,983
Low
42,453
5,633
Low
42,453
5,633
High
69,017
8,805
Moderate
57,813
7,983
Moderate
57,813
7,983
Very High
41,412
4,563
High
69,017
8,805
High
69,017
8,805
Very High
41,412
4,563
Very High
41,412
4,563

High

At this point, the potential realistic plantable
areas have been identified, but not yet
prioritized. While all available planting sites
in Louisville may ultimately be planted over
the next several decades, the trees that are
planted in the next several years, should be
planned for areas in most need, and where
they will provide the most benefits and return
on investment.

Table 23. Prioritization Factors & Results

Very High

Prioritization of Planting Areas

Priority

58

Plan Prioritization

heat island, stormwater mitigation, and
environmental need. The overall results
for these three individual categories are
presented in Table 23.
By overlaying all of these prioritized grid
maps and adding the values at any given
point, a composite prioritization scheme
emerges (Table 24). Additional factors also
considered for this final prioritization include
publicly vs. privately-owned property and
forest fragmentation.1

Very Low
Low
Moderate
High
Very High

Number of
Areas
363,529
42,453
57,813
69,017
41,412

FINAL DRAFT

Acres
38,752
5,633
7,983
8,805
4,563

Table 24. The Composite Planting Site Prioritization
UHI

Priority
Very Low
Low
Moderate
High
Very High

Number of
Areas
277,044
120,293
12,178
107,161
57,548

Acres
3,534
25,479
11,411
16,634
8,678

STORMWATER
It is important to note that parks and other
protected woodland areas were not excluded
from the potential planting areas considered
for three primary reasons.




First, park and woodland trees provide
measurable benefits to nearby
neighborhoods. To exclude them would
make it appear that these neighborhoods
were receiving less benefits than they
are.
Secondly, parks and protected
woodlands are relatively unthreatened
by development. The growing
environment in parks contributes to less
mortality, faster maturity, and longer
service lives of trees planted there.

Priority
Very Low
Low
Moderate
High
Very High

Number of
Areas
272,215
73,140
67,148
107,384
54,337

Acres
2,238
3,606
26,493
25,939
7,461

ALL COMBINED
Priority
Very Low
Low
Moderate
High
Very High

Number of
Areas
186,691
115,961
78,628
142,780
50,164

Acres
1,891
11,435
9,314
31,336
11,761

Very Low
Low
Moderate
High
Very High

1
Planting areas less than 100 square feet were eliminated from this analysis because they were found to not have enough
suitable planting space. This equals a 240-acre difference in planting area.

59


FINAL DRAFT
Plan Costs

Lastly, by including parks in the
neighborhood, census tract, council
district and other land scales, a truer
picture of priority tree planting areas is
revealed. Areas without forested parks
or other protected woodlands nearby
need new trees more than those that have
that resource.

A map book detailing these prioritized
planting areas for each Council District area
has been provided electronically.

Tree Planting Approaches
and Related Costs
With this UTC analysis and prioritization
of plantable areas complete, Louisville has
better information upon which to initiate
projects to achieve canopy goals. Increasing
urban tree canopy means increasing the
number of trees in Louisville. This can be
accomplished in three ways:
Landscape Tree Planting. This solution
generally involves procurement and
installation of 2-3” caliper trees. The
advantages of this method come from a
larger crown at the time of planting, lower
mortality rates, and the variety of aesthetics
and design goals that can be incorporated
into plantings. Disadvantages include the

high costs and intensive labor required, and
a longer establishment period needed after
transplanting. It may also be impractical to
plant large trees on steep topography and in
poor soils, and nursery availability dictates
whether desirable native and urban tolerant
species can be obtained in sufficient quantities.
If the approximately 20,000 acres of RPA’s
(realistic plantable areas) needed to reach the
45% canopy goal in Louisville were planted
with landscape-sized trees, it would require 1.3
million trees. Using the average cost of $480
per tree2,the total cost to achieve 45% UTC
using landscape trees in Louisville would be
$634 million.
Reforestation. Reforestation, or artificial
regeneration, is a technique long practiced by
traditional foresters and land conservationists.
This tree planting solution involves planting
2 to 3-year old, bare-root tree seedlings or
saplings/whips by hand or by machine in areas
currently with a grass, shrub, or bare ground
cover. The advantages are that this method is
less expensive, desirable native tree species
in sufficient quantities are readily available,
re-establishment after planting is quicker so
land can become tree-covered faster, and
it is a method that can be accomplished by
both professional contractors and citizen
volunteers. The disadvantages include higher

mortality rates, protection and weed control
is required for newly planted trees, and until
the trees mature, reforested areas are not
often aesthetically pleasing, especially if the
surrounding area is more developed and
maintained.
Assuming the average cost to reforest one
acre of land is $3503, the cost to reforest the
approximately 20,000 acres of RPA’s (realistic
plantable areas) to achieve 45% UTC in
Louisville would be $7 million.

Bigger isn’t always
better.
When thousands of trees need to be
planted to achieve canopy goals, it is
not always cost-effective or realistic to
plant two-inch caliper landscape trees
everywhere.
The good news is that smaller trees grow
substantially faster. The smaller the tree
is at planting, the faster it will establish
and therefore increase in size. This means
that sapling-size native species will create
canopy faster and less expensively.
It is important to keep reforestation and
smaller landscape trees in mind when
working to reach canopy goals efficiently.

Cost for tree and installation is at a retail rate, and was provided by the City of Louisville.
Cost is based on a general estimate by Timberlands Unlimited Inc. and includes site preparation, tree seedlings, labor, and equipment. This is not an exact cost but one suitable to reach approximate costs.
Source: http://www.timberlandsunlimited.com/reforestation.php

2
3

60

FINAL DRAFT
Plan Costs

Natural Regeneration. As the term
suggests, natural regeneration is simply
allowing nature to take its course.
Louisville’s natural heritage is forestland.
If left undisturbed by human activities,
the vast majority of all land would revert
back to native woodlands. The advantages
are that this costs no money, involves no
labor, and native trees would reappear in
the landscape. The disadvantages are that
while trees regenerate, aesthetics are often
an issue, and competition from exotic and
invasive weeds, shrubs, and trees (such as
honeysuckle and callery pear) may require
chemical, mechanical, or manual removal
and intervention.
Table 25 compares the costs of each
method if only one tree planting method
was chosen to achieve various target
canopy goals.
A Combination of Methods. Clearly, it is
impractical to use only one tree planting
method exclusively to achieve an increase
to 40%, 45%, or even the maximum
potential of 63% tree canopy cover in
Louisville. For instance, it is unreasonable
to expect over 4 million landscape trees
will be planted at a cost of over $2 billion
in the next decade. To be as efficient and
realistic as possible, a strategy should be
developed that involves a combination

Table 25. Costs To Achieve Canopy Goals Per Method
Add'l Canopy Required to Meet Goal
Landscape Trees Method
Reforestation Method

40% Canopy

45% Canopy

63% Canopy
(Max)

7,319 acres

20,041 acres

66,078 acres

$231,683,382

$634,399,050

$2,090,716,327

$2,561,650

$7,014,350

$23,127,447

$0

$0

$0

Natural Regeneration Method

of these three tree planting methods and is
based on land use, budget, and aesthetic
considerations.
A further, higher-level, and detailed land use
analysis is needed to determine areas most
suitable for each of the three tree planting
methods. A list of suggested areas suitable for
each method is provided at below.

When a “tree planting suitability” analysis is
complete, conversations with land owners and
stakeholder groups can then occur and result
in developing tree planting projects with
clear goals, roles, budgets, and other needed
resources. Such a “master tree planting action
plan” will define these projects and can guide
all landowners in a coordinated effort to reach
UTC goals using the most appropriate method
for the site and resources available.

Planting Method Suitabilities
Landscape Trees:
Streets
Suburban residential yards
Maintained park areas
Parking lots
Maintained commercial grounds
Cemeteries
School yards

Reforestation or Natural Regeneration:
Excess road rights-of-way
Urban vacant lots
Stream and river corridors
Idle/unused farmland
Excess industrial land
Naturalized park areas
Steep hillsides

61

FINAL DRAFT

Plan Calculator

UTC Calculator Tool. Where planting
landscape sized trees is required or needed,
the UTC Calculator tool can help determine
the number of trees needed and estimate
the cost of those trees. Developed by Davey
Resource Group, the Urban Tree Resource
Analysis and Cost Estimator (UTRACE) tool
utilizes current baseline percentages from the
UTC assessment to generate possible planting
scenarios. The tool is used to estimate future
tree plantings to attain a particular canopy
goal set by the user. The UTC Calculator
is most useful on smaller scales, such as
neighborhoods, business districts, or census
tracts where landscape trees would likely be
planted, but can also be used on large scales
such as countywide or large watersheds as
needed.
Louisville has received a customized, fully
adjustable version of the UTRACE tree canopy
calculator, allowing the Louisville Metro
Government and regional partners to plan
and consider additional planting strategies as
conditions change or priorities shift.

The UTC calculator
tool provides estimated
planting numbers and
costs for achieving
canopy goals.

62

FINAL DRAFT

Private and Public

Public and Private Property
Tree Planting
Using the land use designations in Louisville,
“public property” was considered the
combination of parks & open space, public/
semi-public, and rights-of-way. The remaining
designations were considered “private
property.” Table 26 presents some of the
summary statistics between these two land
ownership types.
Using the UTC goals of 40% and 45% canopy
cover, and the statistics based on these
designations, it would appear that planting all
realistic plantable areas on public property
would meet these goals and actually exceed
them (assuming no further canopy loss, and
not accounting for EAB effects). However, it
is logical to assume that parks & open space
acreage likely needs to remain open for
future recreational fields and other types of
desirable natural habitats, such as meadows
and prairies. Pervious surface areas in
public/semi-public lands may be needed for
facilities, schools, or other uses for the public
good and welfare. And, although trees can be
planted on interstate and state route public
rights-of-way, these areas are considered a
last resort in many locations due to safety
considerations and the poor soil quality for
growing trees.

Consequently, it should be noted that there is
greater opportunity and need for significant
participation from private property owners to
contribute to canopy increases beyond 40%.
It is also very likely that the highest numbers
of ash trees in Louisville are on privatelyowned land, therefore planting on private
property will likely become a high priority in
the next five years.
The success of reaching UTC goals depends
not only on governments planting trees on
public lands, but on a cooperative publicprivate initiative. Creating public-private
partnerships will include encouraging

Who owns it?
Who owns the land in
Louisville?

Who owns
Louisville's current
canopy?

Who owns the
realistic potential
planting areas (RPAs)
in Louisville?

community participation, training volunteers,
creating and supporting volunteer
organizations, and educating property
owners. Rewarding, or incentivizing, private
property owners for any positive support for
this endeavor can lead to greater success and
likelihood of reaching the stated UTC goals.
Louisville cannot achieve its UTC goals without
the support of its residents and businesses,
so that everyone can enjoy the many social,
environmental, and economic benefits of trees.

Table 26. Land Ownership
Acres

% of Louisville

Private

172,081

69%

Public

74,335

31%

Acres

% of Canopy

Private

67,684

71%

Public

26,422

29%

Acres

% of RPAs

Private

47,811

73%

Public

18,036

27%

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RECOMMENDATIONS
& NEXT STEPS
Louisville Urban Tree Canopy Assessment

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Recommendations
& Next Steps
2015

Louisville Urban Tree
Canopy Assessment

Louisville’s urban tree canopy assessment
and analysis provide a solid foundation
for sustainable solutions to existing urban
challenges.

Recommendations in this section are
categorized in three broad areas:


Caring for Existing Trees

Although the obvious solution to losing
canopy is to plant more trees, a long-term
solution requires more comprehensive efforts,
including tree preservation.



Planting New Trees



Establishing a Supportive
Framework to build and maintain
a sustainable urban tree canopy.

Answers to Louisville’s urban challenges (heat
stress, combined sewer overflows, ash tree
loss, etc.) will require further analysis of the
drivers and barriers influencing policy and
land use decisions related to the urban forest.
And it will require a multifaceted approach
inclusive of new or revised policies, programs,
and well-defined strategic action plans to
ensure future successes. Policy changes,
education, and partnerships will all be crucial
to a turnaround in Louisville’s tree canopy.

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Recommendations

Caring for
Existing
Trees

Planting
New Trees

Caring for Existing Trees
One key for success in reaching canopy goals
is to protect the existing canopy. Current
canopy should be protected and maintained
in a safe and high-functioning condition so
existing mature trees have the longest service
lives possible. In doing so, tree canopy
benefits will be maintained for decades, giving
newly planted trees time to mature.
1. Tree preservation ordinances that reduce
tree canopy loss and encourage land use
planning that supports reforestation goals on
development properties should be considered.
The Maryland Forest Conservation Act (http://
www.dnr.state.md.us/forests/programapps/
newFCA.asp) and the Fairfax County, Virginia
Tree Protection Ordinance (http://www.
fairfaxcounty.gov/dpwes/publications/pfm/
chapter12.pdf ) are two good examples
recommended for further study.

Supportive
Efforts

2. Review and compare all landscape and
zoning codes, ordinances, policies and
guidelines (in all land uses) to current industry
standards for tree planting, species lists, and
tree protection.
3. Consider empowering homeowner
associations in new residential developments
with the responsibility of maintaining trees
within the public rights-of-way and within the
development to minimize future maintenance
impacts on municipal budgets and operations.
4. Promote the use of conservation easements
to protect critical forest areas.
5. Routinely maintain public trees, and
encourage private property owners to do so as
well. Timely routine maintenance is important
for maximizing tree health and longevity, for
identifying and correcting defects or hazardous
conditions that can threaten public safety,

Tree
Canopy
Progress

and for monitoring the tree population
for destructive forest pests and diseases
such as emerald ash borer. Consider
performing timber stand improvement
projects, such as removing diseased trees
and invasive plants in forested areas for
improved forest health.
6. Promote the treatment of ash trees
where appropriate to preserve the benefits
of their collective canopy while new trees
are established.
7. Monitor landscape and woodland trees
for the presences of insect and disease
issues, particularly for Asian long-horned
beetle.

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Recommendations

Planting New Trees
Increasing tree canopy in Louisville requires
long-term dedication and significant efforts
of local governments, non-profits, and private
landowners to plant new trees. Specific areas
need additional trees to mitigate stormwater
issues and urban heat island effects, but all
areas and all people will ultimately benefit
from each tree planted. The important task
at hand is to plant more trees and provide
appropriate follow-up care so the majority of
these new trees reach maturity and provide
the greater canopy needed to maximize the
ecosystem and economic benefits.

with landscape trees, reforestation and/or
natural regeneration. Then create a master tree
planting action plan on a council, sewershed or
other Louisville subdivision level.

are created, then the trees can be planted and
maintained within that easement to increase
tree canopy where it might not otherwise be
possible.

11. Plant trees in local business districts to
not only provide increases in overall canopy
in these areas, but also to gain the economic
benefits trees afford business owners.

13. Consider implementing parking lot
greenspace and stormwater management
policies that maximize tree canopy and
minimize surface runoff.

12. If neighborhoods lack sufficient space
in the public rights-of-way for tree planting,
then investigate whether landscape or green
infrastructure/stormwater easements can be
created on the private property that adjoins
the street rights-of –way. If such easements

14. Consider adopting reforestation policies
for public lands with supporting funding
that demonstrate a long-term commitment to
growing and sustaining a vibrant urban forest.
Review policies and ordinances that protect
trees or require reforestation as part of the

8. Focus landscape tree planting and
reforestation projects in the next five years
in areas designated as Very High Priority,
particularly from the composite priority
analysis provided in this assessment.
9. Plan urban heat island-related tree planting
initiatives or policies that are informed by
both surface temperature differentials and
the comprehensive assessment of heat
vulnerability of citizens based on the results
of the Georgia Institute of Technology UHI
study.
10. Perform a tree planting suitability analysis
for areas/parcels to determine whether tree
planting can or should be accomplished

Right-of-way tree planting.
Image Source: LouisvilleKY.gov

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Recommendations

development process to assist in supporting
Louisville’s tree canopy and sustainability
goals. (As these types of policies can
impact site designs and project costs, a
well-educated public supportive of new
requirements will be needed.)
15. Establish a street tree planting program
that includes a focus on residential streets
when public right-of-way space allows.
16. Consider undertaking state route and
interstate reforestation projects on excess,
mowed areas where public safety or sight
line visibility is not hindered.
17. Include tree planting guidelines for new
right-of-way construction and infrastructure
projects.
18. Seek opportunities to convert
impermeable space such as asphalt
playgrounds, under-utilized basketball or
tennis courts, and abandoned structures to
permeable space with trees.
19. Develop and implement streetscape
design standards that increase available
rooting space, capture street runoff and
improve site growing conditions for large
shade trees in densely developed areas.
Consider focusing on the central business
district and larger commercial areas with

high percentage of impervious surfaces and
heat island conditions.

Relating and Supporting
Efforts

20. Target tree planting in hot spot areas to
address this county-wide issue.

Planting and maintaining trees will not
be successful without supporting efforts,
such as professional community forest
planning, education campaigns, funding
raising, forging new partnerships and
strengthening existing ones, further GIS
and data analysis, and field monitoring.
Louisville Metro Government and
its partners should assess existing
capabilities and build its capacity to
manage a large tree population.

21. Plant more landscape trees and/or
perform reforestation in the sewersheds (CSOs
#27,#142, #155,#160) with the least amount
of canopy, and in the sewersheds reported to
have the most problems, particularly CSOs
#82, #106, and #137 where there is the least
impervious surface percentage which thereby
gives the greatest opportunity to plant trees.
22. Review opportunities to incentivize tree
planting on private property including costshare programs or stormwater fee credits.
23. Connect patch canopy areas where feasible
to larger forested areas to create greenways,
wildlife corridors, and ultimately more core
canopy areas.
24. Establish tree planting goals for all 83
suburban cities in Louisville with the results of
this analysis.

25. Engage, educate and support private
action. As 72% of the existing urban tree
canopy in Louisville is privately owned,
developing and expanding an effective
outreach campaign to educate and
engage the public in support of programs
and policies that sustain a healthy and
vibrant urban forest is a critical step in
achieving canopy goals.
26. Support urban forestry advocacy
organizations such as Brightside,
Louisville Grows, and Re-Tree Shively in
their efforts to promote the importance
and need for tree plantings and
increase their outreach and reforestation
capabilities.

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Recommendations

27. Broaden citizen volunteer and training
programs to ensure that the hundreds of
thousands of trees that will need to be planted
over the next 40 years are properly planted
and cared for.
28. Use tree advocacy groups to unify public
messaging and maintain consistency with
Louisville Metro Government policy by
coordinating the efforts of these organizations.
Synergistic benefits and increased collective
effectiveness may be achieved, especially
if the Tree Advisory Commission had more
authority beyond an advisory capacity.

29. Create public education programs
that build upon tree benefits that people
intuitively enjoy but do not consciously think
about. These efforts will help drive home the
importance and benefits of urban trees as
sustainable solutions to Louisville’s challenges.
Once the public begins to actively think
about the tree canopy benefits experienced,
they will be more supportive of tree planting
initiatives and tree preservation policies.

Potential programs include:


Bring attention to issues like urban heat
islands effects and combined sewer
overflows in a way that addresses citizens’
needs and values directly.



Design and customize education and
planting projects to target groups
disproportionately lacking tree canopy, as
determined in the Socioeconomic analysis
section of this study, those groups being
the less educated, property owners of
homes under $100,000 in value, and rental
property owners. Providing or increasing
financial support for volunteer planted
trees in economically disadvantaged
council districts and census tracts is also
recommended.



Use EAB statistics coupled with the
findings in this study as compelling talking
points to spur more public interest.



Publicize the benefits of trees through
media outlets such as radio and billboards.
Arbor Day and Earth Day celebrations are
ideal community events to promote and
demonstrate community tree benefits.
Many communities include free tree
distributions as part of these events.

30. Develop partnerships with nurseries
or cities to grow desirable urban tolerant
shade trees for public distribution. This
is a low cost way to engage the public
and populate the urban forest with trees
that will maximize benefits returned over
their life. Work with nurseries to add tree
canopy benefit information on the tree
tag description at retail outlets so the
public starts thinking about tree benefits
as selection criteria in addition to physical
characteristics (as with small ornamental
trees).
31. Evaluate providing higher density
incentives for developers who incorporate
low impact and ‘green’ design concepts that
increase tree planting, growth and longevity
32. Enhance minimum tree planting
standards for any new residential or
commercial development, including street
trees.
33. Consider launching a county-wide
tree planting initiative, such as Cincinnati’s
Taking Root, Los Angeles’ Million Trees,
and other grassroots-supported initiatives,
possibly centered around an urban heat
island mitigation goal. The initiative could
have a website that enables residents
and cities to report trees planted as a

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70

Recommendations

means of measuring success toward tree
planting goals (both landscape tree plantings
and reforestation projects). The annual
planting goals could be divided amongst the
neighborhoods and suburban cities within
Louisville to support citizen entry and progress
tracking for their respective area. This may
generate healthy intra-city competition that
increases the accuracy of reporting and trees
actually planted.
34. Investigate trends revealed by the
UTC assessment. Louisville Metropolitan
Government now has the ability to do multiple
levels of further analysis as projects and efforts
require it. Possibilities for further analysis
include:


Investigating further and remedying the
significant loss in canopy on residential
land, whether from land development and/
or the decline of mature trees from insects,
diseases, or lack of proper maintenance.
Trees in residential areas provide the
greatest direct benefits to people in terms
of energy conservation, human health,
and property value. The net canopy loss
on residential land is 8%. As single-family
residential is the predominant land use in
Louisville, this loss equates to nearly 6,620
acres of tree canopy.



Explore and identify further opportunities
to promote additional tree planting in
council districts and other geographic
subdivisions like census tracts and CSO
areas reporting low UTC cover

36. Schedule UTC updates in five-year
increments. Because of the predicted ash tree
losses, an update may be needed sooner to
reassess canopy and to evaluate progress
towards reaching long term canopy goals.



Performing multi-layer analyses as
projects require or as the need for
specific information is requested, for
example, by examining canopy by land
use within census tracts and removing
any large parks out of all neighborhoods
to examine and compare just non-park
urban canopy rates.

37. Complete and maintain an accurate
spatial public tree inventory. A public tree
inventory is an important assessment and
management tool needed to identify and
prioritize future planting opportunities within
the street rights-of-way, parks, and other
public properties. It is also equally important



Investigate census tract changes. Assess
local knowledge to establish why sixteen
census tracts had a 20% or greater
decrease in canopy. Then take steps to
reverse that canopy loss, and ensure
other census tracts do not experience
similar losses.

35. Perform further analysis using the UTC
data and i-Tree tools to determine the public
health benefits of tree canopy and tree
plantings. This could be particularly useful
for creating partnerships with public and
private school districts and with the Louisville
Metro Health Department, and achieving the
goals of initiatives such as Healthy Louisville
2020.

Tree inventory technician

Image Source: Davey Resource Group

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Recommendations

from a maintenance perspective of existing
canopy to have accurate information on the
condition and maintenance needs of trees
located on public properties. Trees should
be inventoried, regularly inspected and
maintained for safe public use and enjoyment.
Modern tree inventory and management
software applications also support tree
inspection records, maintenance scheduling,
and maintenance histories on an individual
tree basis.
38. Initiate a tree management plan.
Management plans are important for
characterizing and assessing the forest
population managed and for projecting
maintenance priorities and costs. They can
also include an operations analysis and
specific recommendations in terms of staffing,
equipment and financial resources needed to
accomplish defined goals and objectives.
39. Strive to complete a community forest
master plan. A forest master plan is a
road map, providing detailed information,
recommendations and resources needed to
effectively and proactively manage and grow
tree canopy. Master plans typically include
a more comprehensive analysis of the urban
forest at various scales and useful information
on forest composition, forest condition, forest
stocking density and tree size distributions.

40. Consider implenting an i-Tree ECO
project to confirm the number of ash trees
and the percent canopy at risk for EAB.
This is highly recommended given the
significant public safety, ecological and social
risks associated with emerald ash borer.
Additionally, Louisville Metro government
should consider completing a hyperspectral
analysis to map the location of ash trees to
provide effective outreach and management
of EAB. A spatial ash map can be used to
supplement the Planting Plan mapbook for
future reforestation planning.
41. Define roles within Louisville Metropolitan
Government to accomplish the goals and
many objectives of expanding the tree canopy.
Identifying a central tree authority/project
champion is recommended.
42. Explore creative financing opportunities
for adding trees in densely developed
business, commercial and neighborhood
regions.


Many communities have self-taxed
business improvement districts or
neighborhood tax improvement districts
to fund community improvements such
as tree planting and green stormwater
infrastructure such as rain gardens or bioswales.



Partner with local businesses and
institutions, such as the Louisville
Slugger® brand and history to generate
funding and form partnerships with
MLB to combat EAB and assist with ash
reforestation.



Use the results of this study to seek
grant funding for tree planting and
public education, and to conduct further
analyses, i.e. i-Tree ECO, i-Ped,

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Final Thoughts
Louisville’s tree canopy is a vital asset
covering 37% of the land (26% in urban core)
and providing $330 million in environmental
and socioeconomic benefits every year. The
management of this asset, however, can be
challenging. Simultaneously balancing the
recommendations of experts, the needs of
residents, the pressures of local economics
and politics, the concerns for public safety and
liability issues, the physical aspects of trees,
and the forces of nature and severe weather is
a vitally important task.

Image Source: Davey Resource Group

The Louisville Metropolitan Government
must carefully consider each specific issue
and balance these pressures with a local
knowledge and an understanding of trees
and their needs. If a balance is achieved,
Louisville and Louisville’s unique livability
will grow stronger and the health and safety
of its trees and residents will be maintained.
With the completion of this UTC assessment,
municipal and county leaders can now use
the data to set goals towards increasing the
amount of UTC within Louisville.

Reaching the desired UTC goals will be a
challenge; however, preserving existing
UTC, establishing realistic UTC goals,
and harnessing the maximum amount of
ecosystem benefits by planting largegrowing trees are prudent, responsible, and
rewarding endeavors.

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APPENDICES
Louisville Urban Tree Canopy Assessment

Appendix A
FINAL
DRAFT
Methodologies
Appendix A Contents
Land Cover Classification............................A1
Accuracy Assessment Protocol.....................A2
Demographics & Socioeconomics................A6
Calculating Tree Benefits....................... ......A6
Urban Heat Island Analysis..........................A9
Stormwater Priority Ranking.........................A9
PotentialTree Planting Estimates..................A10
Tree Planting Plan & Prioritization..............A11

Land Cover Classification
Davey Resource Group utilized an objectbased image analysis (OBIA) semi-automated
feature extraction method to process and
analyze current high-resolution color infrared
(CIR) aerial imagery and remotely-sensed
data to identify tree canopy cover and land
cover classifications. This process utilized
NAIP imagery (National Agriculture Imagery
Program) from the summer growing seasons
of 2012, 2008 and 2004. The use of imagery
analysis is cost-effective and provides a
highly accurate approach to assessing your
community’s existing tree canopy coverage.
This supports responsible tree management,
facilitates community forestry goal-setting,
and improves urban resource planning
for healthier and more sustainable urban
environments.

Advanced image analysis methods were
used to classify, or separate, the land cover
layers from the overall imagery. The semiautomated extraction process was completed
using Feature Analyst™, an extension of
ArcGIS®. Feature Analyst uses an objectoriented approach to cluster together objects
with similar spectral (i.e., color) and spatial/
contextual (e.g., texture, size, shape, pattern,
and spatial association) characteristics.
The land cover results of the extraction
process was post-processed and clipped to
Louisville’s project boundaries prior to the
manual editing process in order to create
smaller, manageable, and more efficient file
sizes. Secondary source data, high-resolution
aerial imagery provided by Louisville Metro
Government, and custom ArcGIS® tools were
used to aid in the final manual editing, and
quality assurance/quality checking (QA/QC)
processes. The manual QA/QC process was
implemented to identify, define, and correct
any misclassifications or omission errors in the
final land cover layer.

soil, shadows). Water samples are not always
needed since hydrologic data are available
for most areas. Training data for impervious
features was provided by the Louisville
Metropolitan Government.

Classification Workflows

6) Edit the impervious layer such as roads,
buildings, parking lots, etc. to reflect actual
impervious features.

1) Prepare imagery for feature extraction
(resampling, rectification, etc.), if needed.
2) Gather training set data for all desired land
cover classes (canopy, impervious, grass, bare

3) Extract canopy layer only; this decreases
the amount of shadow removal from large tree
canopy shadows. Fill small holes and smooth to
remove rigid edges.
4) Edit and finalize canopy layer at 1:2000
scale. A point file is created to digitize-in small
individual trees that will be missed during
the extraction. These points are buffered to
represent the tree canopy. This process is done
to speed up editing time and improve accuracy
by including smaller individual trees.
5) Extract remaining land cover classes using
the canopy layer as a mask; this keeps canopy
shadows that occur within groups of canopy
while decreasing the amount of shadow along
edges.

7) Using canopy and actual impervious
surfaces as a mask; input the bare soils training
data and extract them from the imagery.
Quickly edit the layer to remove or add any

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FINAL DRAFT

Methodologies

features. Davey Resource Group tries to delete
dry vegetation areas that are associated with
lawns, grass/meadows, and agricultural fields.
8) Assemble any hydrological datasets, if
provided. Add or remove any water features to
create the hydrology class. Perform a feature
extraction if no water feature datasets exist.
9) Use geoprocessing tools to clean, repair,
and clip all edited land cover layers to remove
any self-intersections or topology errors that
sometimes occur during editing.
10) Input canopy, impervious, bare soil, and
hydrology layers into Davey Resource Group’s
Five-Class Land Cover Model to complete
the classification. This model generates the
pervious (grass/low-lying vegetation) class by
taking all other areas not previously classified
and combining them.
11) Thoroughly inspect final land cover
dataset for any classification errors and
correct as needed.
12) Perform accuracy assessment. Repeat Step
11, if needed.
Automated Feature Extraction Files
The automated feature extraction (AFE) files
allow other users to run the extraction process
by replicating the methodology. Since Feature
AnalystTM does not contain all geoprocessing

operations that Davey Resource Group utilizes,
the AFE only accounts for part of the extraction
process. Using Feature AnalystTM, Davey
Resource Group created the training set data,
ran the extraction, and then smoothed the
features to alleviate the blocky appearance. To
complete the actual extraction process, Davey
Resource Group uses additional geoprocessing
tools within ArcGIS®. From the AFE file results,
the following steps are taken to prepare the
extracted data for manual editing.
1) Davey Resource Group fills all holes in the
canopy that are less than 30 square meters. This
eliminates small gaps that were created during
the extraction process while still allowing for
natural canopy gaps.
2) Davey Resource Group deletes all
features that are less than 9 square meters
for canopy (50 square meters for impervious
surfaces). This process reduces the amount
of small features that could result in incorrect
classifications and also helps computer
performance.
3) The Repair Geometry, Dissolve, and
Multipart to Singlepart (in that order)
geoprocessing tools are run to complete the
extraction process.
4) The Multipart to Singlepart shapefile is
given to GIS personnel for manual editing to

add, remove, or reshape features.

Accuracy Assessment
Protocol
Determining the accuracy of spatial data is
of high importance to Davey Resource Group
and our clients. To achieve to best possible
result, Davey Resource Group manually edits
and conducts thorough QA/QC checks on
all urban tree canopy and land cover layers.
A QA/QC process will be completed using
ArcGIS® to identify, clean, and correct any
misclassification or topology errors in the
final land cover dataset. The initial land cover
layer extractions will be edited at a 1:1500
quality control scale in the urban areas and
at a 1:2500 scale for rural areas utilizing the
most current high-resolution aerial imagery
to aid in the quality control process.
To test for accuracy, random plot locations

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Methodologies

are generated throughout the city area of
interest and verified to ensure that the data
meet the client standards. A 3x3 grouping of
pixels will be compared with the most current
NAIP high-resolution imagery (reference
image) to determine the accuracy of the final
land cover layer. Points will be classified
as either correct or incorrect and recorded
in a classification matrix. Accuracy will be
assessed using four metrics: overall accuracy,
kappa, quantity disagreement, and allocation
disagreement. These metrics are calculated
using a custom Excel spreadsheet.
Land Cover Accuracy
The following describes Davey Resource
Group’s accuracy assessment techniques and
outlines procedural steps used to conduct the
assessment.
1. Random Point Generation. Using ArcGIS,
1,500 random assessment points are
generated. These points are utilized as “center
points” of 3x3 pixel groupings. A box is drawn
around the nine-pixel grouping. The 1,500
randomly generated groupings are used
for the accuracy assessment. Using a 3x3
grouping of pixels provides more information
for the accuracy assessment since adjacent
pixels are also looked at, which increases the
number of pixels assessed since nine pixels
are assessed instead of just a single pixel.

This method reduces the weight of the center
pixel from 1 to 1/9 since the 3x3 grouping is
assessed as a whole.
2. Point Determination. Each individual pixel
of the 3x3 grouping is carefully assessed by
the GIS analyst for likeness with the aerial
photography. The number of pixels for each
land cover type is recorded. The land cover
class with the most pixels represented in the
pixel grouping is determined to be the correct
land cover class, unless visually disputed on
high-resolution sub-meter imagery. To record
findings, two new fields, CODE and TRUTH,
are added to the accuracy assessment point
shapefile. CODE is a numeric value (1–5)
assigned to each land cover class (Table 1)
and TRUTH is the actual land cover class as
identified according to the reference image.
If CODE and TRUTH are the same for all nine
pixels assessed, then the point is counted
as a correct classification. Likewise, if none
of the pixels assessed match, then the point
is classified as incorrect. If the location has
been 100% egregiously misclassified (all nine
App. Table 1. Land Cover Code Values
Land Cover
Code
Classification
Value
Tree Canopy
1
Impervious
2
Pervious
3
Bare Soil
4
Open Water
5

pixels incorrect), then the results have the same
outcome as using just a single pixel. The same is
true for a correct classification.
In most cases, distinguishing if a point is
correct or incorrect is straightforward. Points
will rarely be misclassified by an egregious
classification or editing error. Often incorrect
points occur where one feature stops and the
other begins. Using nine pixels for the accuracy
assessment instead of only 1 pixel allows for
better identification of transitional pixels and
assignment of varying degrees of correctness.
For example, if the center pixel of the nine-pixel
box is considered incorrect, the other 8 pixels
surrounding it may still be classified correctly.
Thus, instead of the accuracy of this location
being completely correct or completely
incorrect, it can be classified as mostly correct
as opposed to being classified completely
incorrect.
3. Classification Matrix. During the accuracy
assessment, if a point is considered incorrect, it
is given the correct classification in the TRUTH
column. Points are first assessed on the NAIP
imagery for their correctness using a “blind”
assessment—meaning that the analyst does not
know the actual classification (the GIS analyst is
strictly going off the NAIP imagery to determine
cover class). Any incorrect classifications
found during the “blind” assessment are
scrutinized further using sub-meter imagery
provided by the client to determine if the

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A4

Methodologies

App. Table 2. Classification Matrix

Reference Data

Classes
Tree Canopy
Impervious
Grass/Vegetation
Bare Soils
Water
Column Total
User's Accuracy
Errors of Commission

Tree
Canopy
529
2
18
2
1
552
95.83%
4.17%

Grass &
Impervious
Low-Lying
Surfaces
Vegetation
7
21
340
23
10
465
1
4
0
2
358
515
94.97%
90.29%
5.03%
9.71%

point was incorrectly classified due to the
fuzziness of the NAIP imagery or an actual
misclassification. After all random points are
assessed and recorded; a classification (or
confusion) matrix is created. The classification
matrix for this project is presented in Table
2 above. The table allows for assessment of
user’s/producer’s accuracy, overall accuracy,
omission/commission errors, kappa statistics,
allocation/quantity disagreement, and
confidence intervals (Table 3).
4. Following are descriptions of each statistic
as well as the results from some of the
accuracy assessment tests.
Overall Accuracy. Percentage of correctly
classified pixels; for example, the sum of
the diagonals divided by the total points
((529+340+465+20+54)/1,500 = 93.87%).
User’s Accuracy – Probability that a pixel
classified on the map actually represents that

Bare
Soils

Open
Water

Row
Total

Producer's
Accuracy

Errors of
Omission

0
0
0
20
1
21
95.24%
4.76%

0
0
0
0
54
54
100.00%
0.00%

557
365
493
27
58
1,500

94.97%
93.15%
94.32%
74.07%
93.10%

5.03%
6.85%
5.68%
25.93%
6.90%

Overall Accuracy
Kappa Coefficient

93.87%
0.9112

category on the ground (correct land cover
classifications divided by the column total
[529/552 = 95.83%]).
Producer’s Accuracy. Probability of a reference
pixel being correctly classified (correct land
cover classifications divided by the row total
[529/557 = 94.97%]).
Kappa Coefficient. A statistical metric used
to assess the accuracy of classification data.
It has been generally accepted as a better
determinant of accuracy partly because it
accounts for random chance agreement. A
value of 0.80 or greater is regarded as “very
good” agreement between the land cover
classification and reference image.
Errors of Commission. A pixel reports the
presence of a feature (such as trees) that,
in reality, is absent (no trees are actually
present). This is termed as a false positive. In
the matrix above (Table 2), we can determine

that 4.17% of the area classified as canopy is
most likely not canopy.
Errors of Omission. A pixel reports the
absence of a feature (such as trees) when,
in reality, they are actually there. In the
Omission/Commission Errors matrix (next
page), we can conclude that 5.03% of all
canopy classified is actually present in the
land cover data.
Allocation Disagreement. The amount of
difference between the reference image
and the classified land cover map that is
due to less than optimal match in the spatial
allocation (or position) of the classes.
Quantity Disagreement. The amount of
difference between the reference image and
the classified land cover map that is due to
less than perfect match in the proportions (or
area) of the classes.

actually present). This is termed as a false positive. In the matrix below, we can determine that 4.17% of the area classified
as canopy is most likely not canopy.

FINAL DRAFT

A5

Methodologies

Errors of Omission – A pixel reports the absence of a feature (such as trees) when, in reality, they are actually there. In the
matrix below, we can conclude that 5.03% of all canopy classified is actually present in the land cover data.
App. Figure 1. Omission/Commission Errors Matrix

Land Cover Class

Confidence Intervals. A confidence
interval is a type of a population
parameter and is used to indicate the
reliability of an estimate. Confidence
intervals consist of a range of values
(interval) that act as good estimates
of the unknown population parameter
based on the observed probability
of successes and failures. Since
all assessments have innate error,
defining a lower and upper bound
estimate is essential.

Commission or Loss

Agreement or Persistence

Omission or Gain

Water
Bare Soils
Grass/Vegetation
Impervious
Tree Canopy
0

5

10

15

20

25

30

35

40

45

Percent of Study Area

App. Table 3. 95% Confidence Intervals, Accuracy Assessment, and Statistical Metrics Summary
Figure 1. Omission/Commission Errors
Confidence Intervals
Class

Lower

Acreage

Percentage

56,033

22.00%

21.90%

22.10%

Overall Accuracy =

10,113

4.00%

3.90%

4.00%

Quantity Disagreement =

User's
Accuracy

Lower Bound

Upper
Bound

Producer's
Accuracy

Lower Bound

Upper Bound

Tree Canopy
Davey Resource Group
Impervious Surfaces

95.80%

95.00%

96.70%

95.00%

94.00%

95.90%

95.00%

93.80%

96.10%

93.20%

91.80%

94.50%

Grass & Low-Lying Vegetation

90.30%

89.00%

91.60%

94.30%

93.30%

95.40%

Bare Soils

95.20%

90.60%

99.90%

74.10%

65.60%

82.50%

Open Water

100.00%

100.00%

100.00%

93.10%

89.80%

96.40%

Tree Canopy
Impervious Surfaces

Upper Bound

Boundof difference between the reference image and the classified land cover map that is
Allocation Disagreement – The amount
Statistical Metrics Summary
94,462
37.10%
37.00%
37.20%
due to less than optimal match in the spatial allocation
(or position) of the classes.
93.87%

Quantity Disagreement
– The amount
of difference
between the reference image
andCoefficient
the classified
land
cover map that is
0.9112
Grass & Low-Lying Vegetation
88,525
34.80%
34.70%
34.90%
Kappa
=
due to less than
proportions2.10%
(or area) of the classes. Allocation Disagreement =
5%
Bare Soils
5,316perfect match
2.10% in the2.10%
Open Water
Total
Accuracy Assessment

1%

Confidence Intervals – A confidence interval is a type of interval estimate of a population parameter and is used to indicate
254,449
100.00%
the reliability of an estimate. Confidence intervals consist of a range of values (interval) that act as good estimates of the

Class

October 2013

A6

FINAL DRAFT

Demographics &
Socioeconomic Data

App. Table 4. Demographic Data Sources
Table
Variable
Number
Table Description
Age
B01001
Age of Population
Education Level
B15001
Educational Attainment Population 18+
Ethnicity
B02001
Ethnicity of Population
Median Income
B19013
Median Income of Population
Building Value
B25075
Value of Buildings
Building Age
B25034
Year Structure Built
Renter Occupied
B25003
Tenure of Occupied Housing Units
Owner Occupied
B25003
Tenure of Occupied Housing Units
Single Family Homes B25024
Units in Structure(1-Detached)

Methodologies

Data acquired for the socioeconomic analysis
was provided by the U.S. Census Bureau at
the census tract and census block levels,
specifically 2006-2010 American Community
Survey 5-Year Estimates. Table 4 lists exact U.S.
Census table used.

How Tree Canopy Benefits Are
Calculated
Air Quality. The i-Tree Canopy v6.1 Model
was used to quantify the value of ecosystem
services for air quality. i-Tree Canopy was
designed to give users the ability to estimate
tree canopy and other land cover types within
any selected geography. The model uses the
estimated canopy percentage and reports air
pollutant removal rates and monetary values
for carbon monoxide (CO), nitrogen dioxide
(NO2), ozone (O3), sulfur dioxide (SO2), and
particulate matter (PM) (Hirabayashi 2014).
Within the i-Tree Canopy application, the U.S.
EPA’s BenMAP Model estimates the incidence
of adverse health effects and monetary values
resulting from changes in air pollutants
(Hirabayashi 2014; US EPA 2012). Different
pollutant removal values were used for urban
and rural areas. In i-Tree Canopy, the air

pollutant amount annually removed by trees
and the associated monetary value can be
calculated with tree cover in areas of interest
using BenMAP multipliers for each county in
the United States.
To calculate ecosystem services for the
study area, canopy percentage metrics from
UTC land cover data performed during
the assessment were transferred to i-Tree
Canopy. Those canopy percentages were
matched by placing random points within
the i-Tree Canopy application. Benefit values
were reported for each of the five listed air
pollutants.
Carbon Sequestration. The i-Tree Canopy
v6.1 Model was used to quantify the value of
ecosystem services for carbon storage and

sequestration. i-Tree Canopy was designed
to give users the ability to estimate tree
canopy and other land cover types within
any selected geography. The model uses
the estimated canopy percentage and
reports carbon storage and sequestration
rates and monetary values. Methods on
deriving storage and sequestration can be
found in Nowak et al. 2013.
To calculate ecosystem services for the
study area, canopy percentage metrics from
UTC land cover data performed during
the assessment were transferred to i-Tree
Canopy. Those canopy percentages were
matched by placing random points within
the i-Tree Canopy application. Benefit
values were reported for carbon storage
and sequestration.

A7

FINAL DRAFT

Methodologies

Stormwater & Sewersheds. The i-Tree Hydro
v5.0 (beta) Model was used to quantify the
value of ecosystem services for stormwater
runoff. i-Tree Hydro was designed for users
interested in analysis of vegetation and
impervious cover effects on urban hydrology.
This most recent beta version (v5.0) allows
users to report hydrologic data on the city
level rather than just a watershed scale giving
users more flexibility. For more information
about the model, please consult the i-Tree
Hydro v5.0 manual (www.itreetools.org).
To calculate ecosystem services for the
study area, land cover percentages derived
for Louisville were used as inputs into the
model. Precipitation data from 2005 was
selected within the model as that year closely
represented the average rainfall (45.5”) for
the City of Louisville (NOAA 2014). Model
simulations were run under a Base Case as
well as an Alternate Case. The Alterative
Case increased canopy by 1% and assumed
that impervious and vegetation cover would
decrease by 0.5% equally as plantings would
ultimately reduce these land cover types.
This process was completed to assess the
runoff reduction volume associated with a 1%
increase in tree canopy since i-Tree Hydro
does not directly report the volume of runoff
reduced by tree canopy. The volume (in
cubic meters) was converted to gallons and
multiplied by the current canopy percentage

(37.1%) in Louisville to retrieve the overall
volume reduced by the tree canopy.
Through model simulation, it was determined
that tree canopy decreases the runoff volume
in Louisville by 18,835,266,390 billion gallons
during an average precipitation year. This
equates to approximately 199,397 gallons
per acre of tree canopy (18.8 billion/94,461
acres). To validate the model, the results
were compared to the City of Indianapolis
Municipal Forest Resource Analysis report
(Peper et al. 2008) which detailed the
ecosystem services of trees in the Lower
Midwest STRATUM climate zone (U.S. Forest
Service 2012). This report was consulted
because the City of Louisville is located in
this climate zone and the two cities are less
than 120 miles apart in distance making
their climate and weather patterns similar
in nature. The Indianapolis study found that
approximately 1,752 acres of street tree
canopy reduced runoff volume by roughly
318.9 million gallons or 181,412 gallons per
acre (Peper et al. 2008). On average, the City
of Louisville has about 4.5 more inches of
precipitation annually than does the City of
Indianapolis (45.5” to 41.0”), which can mostly
explain the additional 18,000 gallons of annual
runoff reduction associated with an acre of
tree canopy.

In order to assess runoff reduction volume on
the census tract, council district, and sewershed
level, the 199,397 gallons per acre value was
used since i-Tree Hydro does not directly utilize
boundaries other than watershed and city
limits. To place a monetary value on stormwater
reduction, the City of Louisville provided the
price to treat a gallon of stormwater in 2014
($3.34 per 1,000 gallons).
Energy Savings (Cooling). Trees have a
profound effect on building energy and has
been studies using various methods (Carver
et al. 2004; McPherson and Simpson 2003).
The process of estimating energy (electricity)
savings starts with determining the number
of one-unit structures by vintage (age) class
within each census block group. Vintage refers
to construction type for a building (i.e. average
floor area, floor types, insulation (R-value), and
number of stories) and was broken into three
categories: pre-1950, 1950-80, and post-1980.
Census data obtained from the 2010 American
Community Survey (Table B25024 – UNITS
IN STRUCTURE and Table B25034 - YEAR
STRUCTURE BUILT) was used to determine the
number of one-unit structures. The data was
based on 5-year estimates. Since the number
of one-unit structures differed at the block
group level, the number of one-unit structures
was determined by vintage and block group
by multiplying the percentage of units in

A8

FINAL DRAFT

Methodologies

each vintage by the total number of one-unit
structures in each block group (McPherson et
al. 2013). For each block group, total energy
savings were tallied for each block group using
a function of percent UTC, vintage class, and
energy saving coefficients (McPherson and
Simpson 2003, McPherson et al. 2013).
To provide energy savings for council districts
and sewersheds, block groups were assigned
based on their spatial positioning related to
the block group data. While the boundaries do
not overlay perfectly, it does provide a rough
estimate for these boundaries. Census tracts
were calculated without assigning a block
group because these data nested within each
census tract. The kWh saved were summarized.
The monetary value for energy savings was
valued by summing all estimated kWh saved
for each vintage class and multiplied by the
current 2014 electricity cost priced at $0.08076
per kWh.
Property Values. Many benefits of tree canopy
are difficult to quantify. When accounting
for wildlife habitat, well-being, shading, and
beautification, these services are challenging
to translate into economic terms. In order to
provide some estimation of these additional
services, this report calculated a property
value based on the value of home prices for the
City of Louisville. Limitations to this approach

include determining actual value of individual
trees on a property and extrapolation of
residential trees to other land use categories
(McPherson et al. 2013).
In a study completed in 1988, it was found that
single-family residences in Athens, GA had a
0.88% increase in the average home sale price
for every large front-yard tree on the property
(Anderson and Cordell 1988). Using this study,
the sales price increase was utilized as an
indicator of additional tree benefits. While
home sales vary widely, in 2012, the median
home sales value in the City of Louisville was
$120,575 (“Louisville, Kentucky” 2014). Using
this median sales price and multiplying by
0.88%, the value of a large front-yard tree
was $1,447. To convert this value into annual
App. Table 5. Price Table
Prices for Ecosystem
Services (2014)
Energy
Savings
CO2 Storage
CO2
Sequestration
CO
NO2
O3
SO2
PM10
Rainfall
Interception

Service
Value

$/MWh

80.76

$/Ton

19.43

$/Ton

19.43

$/Ton
$/Ton
$/Ton
$/Ton
$/Ton
$/1,000
gals

1,333.50
851.54
3,645.87
253.92
6,268.44
3.34

benefits, the total added value was divided
by the leaf surface area of a 30 year old shade
tree ($1,447/5,382ft2) which yields a base
value of $0.27/ft2. Using methodology from
McPherson et al. 2013 to convert into units
of UTC, the base value of tree canopy was
determined to be $0.23 ft2 UTC. Since this
value was derived using residential land use
designations, transfer functions were used
to adapt and apply the base value to other
land use categories. To be conservative in
the estimation of tree benefits, the land use
reduction factors calculated property value
at 50% impact for single-family residential
parcels, 40% for multi-residential parcels,
20% for commercial parcels, and 10% for all
other land uses (Table 6). The price per unit
of UTC values were multiplied by the amount
of square feet of tree canopy within each land
use category and summarized countywide,
census tract, council district, and sewershed.
App. Table 6. Land Use Reduction
Transfer Function Values Price per
Land Use
Impact unit of
Category
UTC
Single-Family
Residential
Multi-Family
Residential

50%

$0.12

40%

$0.09

Commercial

20%

$0.05

All Other

10%

$0.02

A9

FINAL DRAFT

Methodologies

Urban Heat Island Analysis &
Hot Spot Detection

hotspots. These hot spots were further analyzed
for potential tree plantings.

Two methods were used to identify hot spots
within the study area: surface temperatures
and impervious to canopy land cover ratios.

Impervious to Canopy Ratio. Another metric
to identify urban heat island within the City
of Louisville was the ratio of impervious
surface to canopy cover in a grid of 100 X 100
meter squares. For each square, the amount
of impervious surface and tree canopy was
calculated. The amount of impervious area was
then divided by the canopy cover yielding a
ratio value for each grid cell. A larger ratio
indicated areas of “hotter” surfaces or the
presence of urban heat islands. These areas
were synonymous with impervious surfaces
such as buildings and parking lots. Small
ratio values (less than 1) had a much greater
presence of tree canopy.

Mapping Surface Temperature. Mapping
Land Surface Temperature (LST) pinpoints
land area with the hottest surfaces. For this
project, Landsat 5 Thematic Mapper satellite
imagery (image date July 5, 2010) was used
to create a 30 x 30 meter LST grid for surface
temperature throughout Louisville using
methods from Sobrino et al 2004, and the
surface temperature grid was converted to
units of Fahrenheit. The temperature grid was
resampled to 5 meter resolution in order to
summarize average surface temperature for
all potential planting sites. Temperature data
was summarized using zonal statistics and
given a ranking from very low to very high
based on average surface temperature.
The land surface temperatures of the study
area for the July 5, 2010 image ranged from
57.9°F to 124.6°F (Mean: 85.9°F and Standard
Deviation: 5.6°F). Hot spots were distinguished
and separated by breaking temperature data
into five ranges using Natural Breaks. Using
this method, temperatures were binned into a
fairly even number of pixels per temperature
range. The highest temperature range
areas (94.5°F – 124.6°F) were designated as

Stormwater Priority Ranking
MSD Sewersheds. Identifying priority locations
for stormwater management was essential
to this project. The City of Louisville’s
Metropolitan Sewer District (MSD) currently has
data which was utilized in the priority ranking
process. MSD contained data which placed a
dollar per square foot of impervious surface
value for each of the 101 sewersheds. The
top 10 MSD sewersheds were identified and
discussed in this report (Table 7).

Stormwater Ranking. During the ranking
process, data derived from the UTC analysis,
data provided by MSD, and environmental
data were used to prioritize census tracts,
council districts, and sewersheds (Table 8). For
location specific problem locations throughout
Louisville, MSD provided data for the past two
years where drainage issues (flooding, erosion,
standing water) had occurred. The datasets
were classified based on the value of “risk”
from 0-4, with 4 posing the highest “risk” of
contributing to stormwater runoff. Variables
were weighted to produce a results grid. The
grid was summarized using zonal statistics by
each feature layer and given an average risk
score. Higher priority areas received a larger
risk score.
App. Table 7. Priority Sewersheds
identified by MSD
Total Value per
Sewershed
Square Foot of
Unit ID
Impervious
Number
Surface
CSO 141
CSO 082
CSO 120
CSO 154
CSO 153
CSO 106
CSO 137
CSO 083
CSO 119
CSO 179

$16.65
$5.00
$3.78
$2.82
$2.67
$2.61
$2.61
$2.51
$2.51
$2.49

A10

FINAL DRAFT

Methodologies

App. Table 8. Stormwater Ranking Weights
Dataset
Weight Source
Drainage Issues
0.35 Metropolitan Sewer District
Impervious Distance
0.25 Urban Tree Canopy Assessment
Slope
0.15 National Elevation Dataset
Floodplain
0.1
Metropolitan Sewer District
Soils
0.1
Natural Resource Conservation Service
Canopy Distance
0.05 Urban Tree Canopy Assessment

Potential Tree Planting
Estimates
Potential Tree Planting Sites. By eliminating
all non-suitable sites described previously,
potential tree counts were estimated. The
number of potential sites was calculated
based on two types of planting sites – pervious
and possible impervious. For each type, the
number of gross and net sites was tabulated.
The gross number was estimated by taking
the area of planting space available (in square
feet) and dividing by a medium-sized 29-ft
crown diameter. This is the same crown size
and area used to approximate the existing tree
counts. The net total of potential planting sites
was calculated by taking the gross number
and multiplying it by the current canopy
percentage over pervious surface and the
current canopy percentage over impervious
surface. During the assessment, it was found
that 50% of all pervious surfaces (excludes
impervious surfaces and water) were covered
by tree canopy and approximately 5% of

impervious surfaces were cover by tree
canopy. Therefore, to find the best estimate
and provide a reasonable count of potential
planting sites, the number of potential trees
in pervious planting areas was multiplied by
50% and the number of potential impervious
sites was multiplied by 5%.
Existing Trees. The number of existing trees
was calculated using an assumed average
crown diameter of 29 feet (661 square
feet) based on the results from the City of
Indianapolis Municipal Forest Resource
Analysis report by Peper et al. 2008 which
found the sampled street trees to have an
average crown diameter of 29 -feet across
all tree species. The area of tree canopy was
divided by the crown area (661 square feet)
to receive the total number of trees. Existing
tree counts were evaluated for block groups,
census tracts, council districts, land use

designations, suburban cities, neighborhoods,
parcels, and sewersheds as well as
countywide. Using the tree counts, additional
metrics for tree density (trees per acre) and
trees per capita were also derived. Trees per
capita were only calculated for block groups,
census tracts, and council districts due to
population data not readily available at other
levels.

A11

FINAL DRAFT

Methodologies

Tree Planting Plan &
Prioritization Methodology

potential) while D soils have slow infiltration
rates (high runoff).

All potential planting sites were not treated
equal as some sites were considered to
be more suitable than others. Through
prioritization, sites were ranked by three
factors: urban heat island effects, stormwater
management and a combination of
environmental sensitivities. Each of the three
factors were weighted evenly.

Slope. Slope is a measure of change in
elevation. It is a crucial parameter in several
well-known predictive models used for
environmental management. A higher degree
of slope increases the velocity of stormwater
runoff causing a greater risk of erosion due to
sheeting, especially if slopes are bare.

Environmental Sensitivities. A number of
features were considered in the environmental
sensitivities factor, including:
Floodplains. A floodplain is an area of land
adjacent to a stream or riverthat stretches
from the banks of its channel to the base of
the enclosing valley walls and experiences
flooding during periods of high discharge.
Floodplains can support particularly rich
ecosystems, both in quantity and diversity.
Protecting them is ecologically important.
Hydrologic Soil Group. Soils are assigned
groups according to the rate of water
infiltration when the soils are not protected by
vegetation, are thoroughly wet, and receive
precipitation from long-duration storms. The
soils have four groups (A, B, C, and D). A
soils have a high infiltration rate (low runoff

Hardscape Proximity. Impervious surfaces
vastly increase the amount of runoff during
storm events. By identifying these locations
and their surroundings, measures can be
taken to reduce the amount of runoff by
planting trees close to hardscapes.
Canopy Proximity. Canopy fragmentation has
many ecological downsides by degrading
the overall health of the trees and wildlife. It
is essential to close as many gaps as possible
and create more connectivity to increase
biodiversity and canopy health.
Road Density. The amount of road density
signifies how much noise and air pollution are
being released in the atmosphere. Controlling
these factors helps maintain quieter
neighborhoods as well as reduced levels of air
pollution emissions such as carbon dioxide,
ozone, and particulate matter.

Population Density. Population density
represents the number of people within a
given area. Having greater amounts of people
within an area attracts the need for more
trees to aesthetically improve the urban
landscape. By planting in areas with higher
population density, there is more return on
investment because more people receive this
benefit.
Each feature was assessed using separate
grid maps. Values between zero and four
(with zero having the lowest runoff risk
potential) were assigned to each feature/grid
assessed. The grids were overlain and the
values were averaged to determine the runoff
risk potential at an area on the map. A runoff
priority ranging from Very Low to Very High
was assigned to areas on the map based on
the calculated average.
Heat Island and Stormwater. The output
grid of values from the environmental
sensitivities was then overlayed with the
urban heat island grid values (based on
the surface temperature data method) and
stormwater priority values, both described
earlier in the appendix, to create the
composite prioritization results.

Appendix
B
FINAL DRAFT
Data Tables & Charts
Appendix B Contents:

Overall Tables
- Council
District & Potential Canopy
Council
Districts:
Existing

Existing / Potential
Canopy Tables by:
Council District......B1
Suburban City........B2
Neighborhood.......B5
Sewershed Data....B8
CSO / Neighborhood
Overlay Map ......B11
Tree Benefits by
Council District....B12
Socioeconomic
Charts..................B13
Action Scenarios
Table....................B16
A complete and
extensive collection
of data tables and
shapefiles have
been delivered
to the Louisville
Metro Government
electronically for future
use and analysis.

District 1
District 2
District 3
District 4
District 5
District 6
District 7
District 8
District 9
District 10
District 11
District 12
District 13
District 14
District 15
District 16
District 17
District 18
District 19
District 20
District 21
District 22
District 23
District 24
District 25
District 26

Size
(acres)
9,389
4,986
4,537
4,153
5,371
3,291
7,956
4,322
6,515
6,410
7,032
8,402
20,928
18,013
4,316
16,158
8,916
7,406
19,935
39,330
7,143
12,991
7,988
6,972
7,702
4,160

% of Study
Area
4%
2%
2%
2%
2%
1%
3%
2%
3%
3%
3%
3%
8%
7%
2%
6%
4%
3%
8%
15%
3%
5%
3%
3%
3%
2%

2004
Canopy
30%
26%
23%
13%
25%
20%
45%
45%
37%
30%
34%
31%
50%
47%
33%
43%
39%
31%
43%
53%
19%
38%
37%
31%
48%
28%

2008
Canopy
28%
23%
23%
12%
23%
19%
42%
43%
35%
28%
33%
29%
48%
46%
32%
42%
38%
29%
41%
52%
17%
37%
36%
30%
46%
27%

2012
Canopy
27%
22%
21%
12%
23%
18%
40%
40%
33%
25%
32%
29%
48%
46%
31%
40%
36%
27%
39%
51%
16%
35%
34%
29%
45%
24%

Rate of
Change
2004 to 2012
-9%
-14%
-9%
-4%
-6%
-12%
-11%
-12%
-11%
-16%
-6%
-5%
-4%
-1%
-6%
-7%
-9%
-10%
-8%
-3%
-17%
-8%
-8%
-7%
-8%
-14%

Additional
Canopy
Potential
25%
32%
33%
16%
19%
22%
24%
22%
20%
27%
29%
32%
26%
22%
25%
23%
31%
28%
26%
20%
25%
34%
38%
36%
30%
29%

Maximum
Canopy
Possible
52%
54%
54%
29%
43%
40%
64%
62%
53%
52%
60%
61%
74%
68%
56%
63%
67%
56%
65%
72%
40%
69%
73%
65%
75%
54%

B2

FINAL DRAFT

Data Tables & Charts

Suburban
Existing
Canopy
Overall
TablesCities:
- Municipalities
- pg &
1 ofPotential
3
% of
Study
2004
2008
Size
(acres)
Area
Canopy Canopy
Anchorage
1,894
0.74%
64%
62%
Audubon Park
209
0.08%
58%
56%
Bancroft
98
0.04%
50%
47%
Barbourmeade
251
0.10%
51%
45%
Beechwood Village
177
0.07%
48%
41%
Bellemeade
180
0.07%
50%
40%
Bellewood
51
0.02%
70%
65%
Blue Ridge Manor
117
0.05%
34%
31%
Briarwood
59
0.02%
40%
34%
Broeck Pointe
43
0.02%
51%
49%
Brownsboro Farm
146
0.06%
61%
56%
Brownsboro Village
46
0.02%
58%
55%
Cambridge
35
0.01%
51%
51%
Coldstream
141
0.06%
32%
23%
Creekside
47
0.02%
46%
39%
Crossgate
34
0.01%
41%
40%
Douglass Hills
845
0.33%
37%
36%
Druid Hills
52
0.02%
67%
65%
Fincastle
133
0.05%
45%
43%
Forest Hills
175
0.07%
30%
27%
Glenview
921
0.36%
69%
69%
Glenview Hills
74
0.03%
50%
48%
Glenview Manor
54
0.02%
48%
44%
Goose Creek
39
0.02%
48%
47%
Graymoor/Devondale
472
0.19%
34%
30%
Green Spring
168
0.07%
50%
49%
Heritage Creek
292
0.11%
19%
23%
Hickory Hill
17
0.01%
27%
27%
Hills and Dales
64
0.03%
57%
56%
Hollow Creek
147
0.06%
49%
48%
Hollyvilla
219
0.09%
60%
59%
Houston Acres
92
0.04%
53%
52%
Hurstbourne
1,146
0.45%
31%
31%

2012
Canopy
57%
48%
45%
43%
33%
36%
53%
30%
32%
46%
57%
46%
48%
19%
38%
35%
34%
56%
40%
26%
60%
37%
40%
43%
27%
49%
24%
22%
55%
41%
57%
50%
29%

Rate of
Change
2004 to 2012
-11%
-17%
-9%
-16%
-31%
-28%
-24%
-12%
-20%
-9%
-7%
-20%
-6%
-41%
-19%
-15%
-7%
-17%
-10%
-12%
-12%
-25%
-16%
-11%
-21%
-2%
24%
-18%
-3%
-15%
-5%
-7%
-7%

Additional
Canopy
Potential
26%
27%
31%
30%
32%
39%
25%
26%
32%
26%
19%
27%
31%
51%
33%
29%
27%
20%
36%
24%
27%
33%
35%
26%
37%
29%
55%
35%
27%
34%
20%
26%
25%

Maximum
Canopy
Possible
83%
75%
76%
73%
65%
75%
78%
56%
65%
72%
76%
73%
79%
70%
70%
64%
62%
76%
77%
50%
87%
71%
76%
68%
64%
77%
79%
57%
82%
76%
78%
76%
54%

FINAL DRAFT

B3

Data Tables & Charts
Overall Tables
- Municipalities
- pg &
2 ofPotential
3
Suburban
Cities:
Existing
Canopy (continued)

Hurstbourne Acres
Indian Hills
Jeffersontown
Kingsley
Langdon Place
Lincolnshire
Louisville
Lyndon
Lynnview
Manor Creek
Maryhill Estates
Meadow Vale
Meadowbrook Farm
Meadowview Estates
Middletown
Mockingbird Valley
Moorland
Murray Hill
Norbourne Estates
Northfield
Norwood
Old Brownsboro Place
Parkway Village
Plantation
Poplar Hills
Prospect
Richlawn
Riverwood
Rilling Fields
Rolling Hills
Seneca Gardens
Shively
South Park View

Size
(acres)
211
1,252
6,372
44
115
29
218,979
2,317
116
34
25
117
18
51
3,264
132
59
85
49
302
74
85
56
128
16
2,514
65
132
150
121
98
2,953
77

% of
Study
Area
0.08%
0.49%
2.50%
0.02%
0.05%
0.01%
86.06%
0.91%
0.05%
0.01%
0.01%
0.05%
0.01%
0.02%
1.28%
0.05%
0.02%
0.03%
0.02%
0.12%
0.03%
0.03%
0.02%
0.05%
0.01%
0.99%
0.03%
0.05%
0.06%
0.05%
0.04%
1.16%
0.03%

2004
Canopy
27%
67%
28%
33%
25%
45%
40%
34%
25%
58%
53%
33%
42%
38%
40%
75%
45%
47%
58%
39%
59%
45%
25%
35%
14%
41%
53%
58%
58%
33%
49%
24%
64%

2008
Canopy
26%
67%
27%
31%
24%
44%
39%
31%
22%
53%
52%
27%
39%
37%
38%
68%
37%
47%
53%
38%
48%
42%
24%
32%
14%
41%
48%
57%
57%
25%
48%
24%
7%

2012
Canopy
25%
64%
26%
29%
23%
41%
38%
30%
19%
50%
46%
23%
39%
31%
35%
70%
34%
46%
46%
31%
44%
40%
21%
28%
13%
40%
34%
56%
54%
23%
44%
22%
28%

Rate of
Change
2004 to 2012
-7%
-5%
-8%
-14%
-8%
-9%
-6%
-14%
-24%
-15%
-13%
-29%
-8%
-18%
-13%
-7%
-26%
-3%
-20%
-20%
-26%
-10%
-16%
-21%
-6%
-3%
-36%
-4%
-7%
-31%
-10%
-9%
-55%

Additional
Canopy
Potential
32%
20%
31%
34%
41%
35%
25%
33%
38%
24%
27%
31%
31%
28%
27%
19%
37%
27%
25%
30%
24%
32%
32%
36%
29%
25%
30%
23%
23%
34%
28%
35%
66%

Maximum
Canopy
Possible
57%
83%
57%
63%
64%
76%
63%
62%
57%
73%
73%
54%
70%
60%
62%
89%
70%
73%
71%
61%
68%
72%
53%
63%
42%
65%
64%
80%
77%
57%
72%
57%
94%

FINAL DRAFT

B4

Data Tables & Charts

Suburban
Cities:
Existing
Canopy (continued)
Overall Tables
- Municipalities
- pg &
3 ofPotential
3

Spring Mill
Spring Valley
St. Matthews
St. Regis Park
Strathmoor Manor
Strathmoor Village
Sycamore
Ten Broeck
Thornhill
Watterson Park
Wellington
West Buechel
Westwood
Wildwood
Windy Hills
Woodland Hills
Woodlawn Park
Worthington Hills

Size
(acres)
35
126
2,771
229
35
65
10
141
29
919
57
412
79
46
567
134
161
158

% of
Study
Area
0.01%
0.05%
1.09%
0.09%
0.01%
0.03%
0.00%
0.06%
0.01%
0.36%
0.02%
0.16%
0.03%
0.02%
0.22%
0.05%
0.06%
0.06%

2004
Canopy
40%
60%
32%
37%
51%
36%
18%
75%
56%
24%
33%
10%
38%
43%
46%
38%
40%
39%

2008
Canopy
39%
55%
30%
37%
47%
34%
18%
71%
55%
21%
29%
11%
33%
41%
45%
34%
35%
38%

2012
Canopy
35%
54%
26%
35%
40%
32%
17%
69%
47%
15%
25%
11%
29%
40%
39%
31%
28%
28%

Rate of
Change
2004 to 2012
-12%
-9%
-19%
-6%
-22%
-12%
-8%
-8%
-16%
-37%
-24%
9%
-24%
-7%
-16%
-20%
-30%
-30%

Additional
Canopy
Potential
33%
22%
28%
33%
28%
31%
24%
24%
25%
29%
35%
24%
38%
31%
33%
36%
36%
40%

Maximum
Canopy
Possible
68%
76%
53%
68%
68%
62%
41%
93%
72%
44%
60%
35%
67%
72%
72%
66%
65%
68%

B5

FINAL DRAFT

Data Tables & Charts

Neighborhoods:
Existing
Potential
Canopy
Overall Tables - Neighborhood
- pg&
1 of
3

Rate of
Additional
2004
2008
2012
Change
Canopy
Size % of Study
(acres)
Area
Canopy Canopy Canopy 2004 to 2012 Potential
Algonquin
763
2%
14%
14%
12%
-13%
26%
Auburndale
392
1%
34%
32%
29%
-16%
40%
Audubon
398
1%
34%
33%
29%
-15%
35%
Audubon Park
206
1%
58%
56%
48%
-17%
27%
Avondale Melbourne Heights
310
1%
37%
35%
29%
-20%
34%
Bashford Manor
355
1%
26%
24%
23%
-11%
29%
Beechmont
925
2%
29%
28%
26%
-10%
32%
Belknap
506
1%
43%
40%
37%
-13%
26%
Bon Air
789
2%
31%
30%
28%
-12%
32%
Bonnycastle
209
1%
46%
44%
41%
-11%
25%
Bowman
811
2%
19%
19%
18%
-9%
18%
Brownsboro Zorn
505
1%
54%
52%
51%
-7%
23%
Butchertown
588
1%
25%
26%
23%
-7%
29%
California
787
2%
16%
14%
13%
-21%
22%
Camp Taylor
267
1%
35%
35%
30%
-14%
30%
Central Business District
758
2%
7%
7%
8%
16%
12%
Cherokee Gardens
251
1%
58%
55%
53%
-9%
24%
Cherokee Seneca
843
2%
58%
56%
55%
-5%
13%
Cherokee Triangle
626
2%
48%
47%
41%
-13%
11%
Chickasaw
779
2%
33%
33%
30%
-10%
32%
Clifton
436
1%
43%
42%
39%
-10%
20%
Clifton Heights
410
1%
43%
43%
40%
-6%
23%
Cloverleaf
464
1%
28%
26%
23%
-20%
42%
Crescent Hill
1,217
3%
41%
39%
37%
-10%
22%
Deer Park
314
1%
27%
27%
24%
-10%
29%
Edgewood
476
1%
33%
21%
16%
-51%
52%
Fairgrounds
693
2%
6%
6%
6%
-1%
26%
Gardiner Lane
190
0%
34%
32%
30%
-13%
29%
Germantown
384
1%
25%
25%
22%
-12%
24%
Hallmark
88
0%
25%
25%
22%
-10%
37%
Hawthorne
281
1%
33%
32%
30%
-9%
32%
Hayfield Dundee
377
1%
39%
37%
34%
-12%
27%
Hazelwood
411
1%
36%
35%
31%
-15%
37%

Maximum
Canopy
Possible
38%
69%
64%
75%
64%
52%
59%
63%
60%
66%
35%
74%
53%
35%
61%
20%
77%
67%
53%
62%
58%
64%
65%
59%
53%
68%
31%
58%
46%
60%
62%
62%
68%

B6

FINAL DRAFT

Data Tables & Charts

Neighborhoods:
Existing
Potential
Canopy (continued)
Overall Tables - Neighborhood
- pg&
2 of
3

Highland Park
Highlands
Highlands Douglass
Hikes Point
Irish Hill
Iroquois
Iroquois Park
Jacobs
Kenwood Hill
Kingsley
Klondike
Limerick
Meadowview Estates
Merriwether
Old Louisville
Paristown Pointe
Park Duvalle
Park Hill
Parkland
Parkway Village
Phoenix Hill
Poplar Level
Portland
Prestonia
Rockcreek Lexington Road
Russell
Saint Joseph
Schnitzelburg
Seneca Gardens
Shawnee
Shelby Park
Smoketown Jackson

Rate of
Additional
2004
2008
2012
Change
Canopy
Size % of Study
(acres)
Area
Canopy Canopy Canopy 2004 to 2012 Potential
375
1%
12%
13%
12%
-2%
27%
117
0%
28%
28%
24%
-13%
20%
412
1%
45%
43%
40%
-12%
26%
573
1%
31%
30%
27%
-13%
32%
256
1%
41%
40%
38%
-6%
20%
423
1%
28%
27%
24%
-14%
35%
878
2%
71%
70%
68%
-4%
13%
451
1%
23%
24%
22%
-2%
32%
331
1%
48%
47%
45%
-7%
28%
46
0%
32%
30%
28%
-14%
33%
524
1%
30%
28%
26%
-13%
35%
145
0%
17%
17%
16%
-6%
24%
41
0%
41%
40%
34%
-18%
30%
166
0%
22%
22%
20%
-9%
26%
767
2%
26%
26%
25%
-6%
15%
43
0%
16%
16%
14%
-12%
20%
582
1%
20%
21%
19%
-6%
33%
643
2%
17%
17%
15%
-13%
25%
521
1%
26%
25%
23%
-9%
25%
56
0%
25%
24%
21%
-16%
32%
373
1%
14%
11%
11%
-22%
17%
776
2%
46%
43%
42%
-9%
23%
1,609
4%
26%
24%
25%
-4%
25%
274
1%
24%
22%
20%
-16%
32%
383
1%
42%
40%
38%
-10%
23%
898
2%
21%
20%
21%
-1%
22%
387
1%
21%
21%
20%
-6%
24%
371
1%
23%
22%
21%
-9%
29%
100
0%
49%
47%
44%
-10%
28%
1,376
3%
37%
35%
35%
-6%
26%
260
1%
20%
20%
19%
-9%
24%
253
1%
17%
17%
16%
-7%
21%

Maximum
Canopy
Possible
39%
45%
65%
58%
58%
60%
81%
54%
73%
61%
61%
40%
64%
47%
40%
34%
51%
40%
48%
53%
27%
65%
50%
52%
61%
43%
43%
50%
71%
60%
42%
37%

B7

FINAL DRAFT

Data Tables & Charts

Neighborhoods:
Existing
Potential
Canopy (continued)
Overall Tables - Neighborhood
- pg&
3 of
3

South Louisville
Southland Park
Southside
Standiford
Strathmoor Manor
Strathmoor Village
Taylor Berry
Tyler Park
University
Wellington
Wilder Park
Wyandotte

Rate of
Additional
2004
2008
2012
Change
Canopy
Size % of Study
(acres)
Area
Canopy Canopy Canopy 2004 to 2012 Potential
496
1%
14%
14%
13%
-5%
18%
436
1%
18%
16%
15%
-16%
36%
589
1%
18%
17%
16%
-12%
27%
175
0%
4%
4%
3%
-23%
8%
36
0%
51%
46%
39%
-22%
28%
67
0%
35%
33%
31%
-12%
30%
662
2%
28%
28%
26%
-7%
29%
329
1%
48%
48%
37%
-24%
19%
522
1%
12%
12%
11%
-9%
16%
57
0%
32%
28%
25%
-23%
35%
237
1%
30%
31%
29%
-2%
25%
348
1%
26%
27%
25%
-2%
30%

Maximum
Canopy
Possible
31%
51%
43%
11%
67%
61%
55%
56%
27%
60%
54%
56%

FINAL DRAFT

B8

Data Tables & Charts
Sewersheds - page 1 of 3

Sewersheds

CSO015
CSO016
CSO019
CSO020
CSO022
CSO023
CSO027
CSO028
CSO029
CSO031
CSO034
CSO035
CSO036
CSO038
CSO050
CSO051
CSO052
CSO053
CSO054
CSO055
CSO056
CSO057
CSO058
CSO062
CSO082
CSO083
CSO084
CSO086
CSO088
CSO091
CSO092
CSO093
CSO104

Stormwater
Rate of
Additional Maximum Impervious Runoff Reduced
2004
2008
2012
Change
Canopy
Canopy
Benefit Value /
Surface %
by Canopy
Size
(acres) Canopy Canopy Canopy 2004 to 2012 Potential
(2012)
(gallons)
Possible
Value ($)
Acre
7,417
23%
22%
21%
-8%
29%
50%
46%
306,012,524
$1,022,082 $137.80
4
33%
35%
24%
-27%
36%
60%
37%
173,595
$580
$159.80
1,095
26%
23%
24%
-5%
26%
50%
46%
52,746,723
$176,174 $160.93
64
13%
12%
11%
-15%
16%
27%
72%
1,411,365
$4,714
$73.54
63
3%
3%
4%
57%
5%
10%
90%
543,685
$1,816
$28.64
15
10%
9%
11%
8%
5%
15%
84%
319,612
$1,068
$70.22
9
2%
1%
1%
-44%
12%
13%
86%
20,634
$69
$8.09
20
10%
11%
11%
8%
5%
16%
84%
436,130
$1,457
$73.36
46
8%
8%
6%
-18%
9%
16%
84%
569,195
$1,901
$41.50
9
31%
33%
30%
-3%
18%
48%
51%
554,520
$1,852
$202.60
5
16%
15%
16%
1%
9%
24%
75%
162,268
$542
$104.94
16
1%
3%
3%
110%
11%
14%
86%
87,068
$291
$18.19
30
7%
7%
8%
23%
6%
14%
85%
486,707
$1,626
$55.10
9
2%
4%
4%
136%
6%
10%
90%
73,870
$247
$27.86
39
6%
7%
7%
16%
6%
13%
86%
545,212
$1,821
$46.37
6
5%
6%
8%
70%
4%
12%
87%
91,845
$307
$52.69
10
4%
3%
6%
36%
13%
19%
80%
109,623
$366
$37.92
35
5%
5%
6%
41%
4%
11%
89%
449,131
$1,500
$43.14
4
5%
11%
13%
171%
2%
15%
85%
101,301
$338
$88.39
16
2%
3%
5%
161%
9%
14%
85%
166,257
$555
$34.80
36
2%
3%
4%
155%
4%
8%
91%
285,188
$953
$26.18
76
12%
11%
11%
-5%
12%
23%
77%
1,656,910
$5,534
$72.83
121
10%
8%
7%
-31%
14%
21%
78%
1,713,101
$5,722
$47.19
107
25%
25%
22%
-9%
35%
57%
41%
4,766,208
$15,919 $149.33
13
37%
39%
35%
-5%
27%
62%
37%
913,135
$3,050
$236.21
30
25%
25%
22%
-11%
18%
41%
58%
1,346,655
$4,498
$147.53
146
27%
27%
23%
-14%
18%
41%
53%
6,703,284
$22,389 $153.07
3
17%
19%
20%
22%
25%
45%
54%
133,607
$446
$135.14
2
14%
23%
19%
38%
21%
41%
59%
86,674
$289
$128.43
14
30%
30%
24%
-19%
31%
55%
43%
689,160
$2,302
$162.64
10
26%
26%
25%
-4%
25%
50%
49%
511,330
$1,708
$165.27
17
9%
10%
9%
-2%
14%
23%
76%
315,623
$1,054
$60.26
69
36%
32%
28%
-23%
33%
61%
37%
3,786,492
$12,647 $184.56

FINAL DRAFT

B9

Data Tables & Charts
Sewersheds - page 2 of 3

Sewersheds (continued)

CSO105
CSO106
CSO108
CSO109
CSO110
CSO111
CSO113
CSO117
CSO118
CSO119
CSO120
CSO121
CSO125
CSO126
CSO127
CSO130
CSO131
CSO132
CSO137
CSO140
CSO141
CSO142
CSO144
CSO146
CSO148
CSO149
CSO150
CSO151
CSO152
CSO153
CSO154
CSO155
CSO160

Stormwater
Rate of
Additional Maximum Impervious Runoff Reduced
2004
2008
2012
Change
Canopy
Canopy
by Canopy
Size
Surface %
(acres) Canopy Canopy Canopy 2004 to 2012 Potential
(2012)
(gallons)
Possible
1,088
26%
25%
24%
-10%
27%
50%
48%
51,362,197
10
66%
66%
43%
-35%
26%
69%
29%
842,860
508
46%
44%
40%
-13%
26%
66%
33%
40,632,983
101
30%
29%
27%
-9%
29%
56%
40%
5,453,744
93
32%
31%
26%
-16%
25%
52%
34%
4,903,903
88
25%
25%
22%
-10%
31%
54%
45%
3,902,025
67
21%
21%
19%
-11%
33%
52%
44%
2,543,846
73
27%
27%
25%
-7%
24%
49%
49%
3,592,755
339
10%
9%
9%
-14%
18%
27%
72%
6,065,291
4
12%
12%
11%
-13%
14%
25%
74%
95,145
15
16%
16%
12%
-24%
18%
30%
68%
367,923
102
13%
10%
10%
-21%
18%
28%
71%
2,079,596
359
46%
41%
40%
-13%
21%
61%
34%
28,831,715
37
59%
51%
44%
-26%
23%
66%
33%
3,258,565
216
41%
40%
36%
-13%
19%
55%
37%
15,505,665
16
14%
14%
13%
0%
12%
25%
73%
431,599
30
28%
29%
24%
-14%
20%
43%
56%
1,436,481
674
42%
41%
38%
-8%
22%
60%
37%
51,670,187
72
27%
26%
23%
-16%
10%
32%
25%
3,239,408
78
27%
27%
23%
-14%
23%
46%
52%
3,592,410
9
11%
11%
10%
-3%
13%
24%
75%
183,740
5
3%
3%
4%
28%
23%
26%
73%
34,719
12
34%
31%
29%
-15%
26%
55%
44%
667,541
98
20%
20%
19%
-6%
24%
43%
56%
3,651,211
26
54%
54%
42%
-22%
27%
69%
30%
2,213,941
418
28%
28%
26%
-9%
20%
46%
51%
21,677,773
2
13%
15%
19%
42%
6%
24%
75%
64,513
245
49%
48%
39%
-21%
23%
62%
33%
19,020,807
242
31%
31%
25%
-20%
19%
44%
45%
11,931,379
41
31%
30%
28%
-8%
23%
52%
47%
2,337,354
35
18%
20%
16%
-8%
35%
51%
47%
1,117,214
5
0%
7%
1%
1262%
14%
15%
84%
14,085
2
0%
0%
1%
9%
10%
89%
3,103

Benefit
Value ($)
$171,550
$2,815
$135,714
$18,216
$16,379
$13,033
$8,496
$12,000
$20,258
$318
$1,229
$6,946
$96,298
$10,884
$51,789
$1,442
$4,798
$172,578
$10,820
$11,999
$614
$116
$2,230
$12,195
$7,395
$72,404
$215
$63,529
$39,851
$7,807
$3,731
$47
$10

Value /
Acre
$157.70
$285.33
$267.39
$180.36
$176.31
$148.89
$126.45
$163.96
$59.74
$71.16
$79.67
$68.33
$268.01
$291.34
$239.73
$89.87
$157.53
$256.07
$149.93
$154.06
$69.93
$24.58
$191.99
$125.04
$282.37
$173.24
$124.33
$258.90
$164.47
$189.58
$107.41
$9.52
$4.59

B10

FINAL DRAFT

Data Tables & Charts

Sewersheds - page 3 of 3

Stormwater
Rate of
Additional Maximum Impervious Runoff Reduced
2004
2008
2012
Change
Canopy
Canopy
Size
Surface %
by Canopy
(acres) Canopy Canopy Canopy 2004 to 2012 Potential
(2012)
(gallons)
Possible
CSO161
1
15%
14%
16%
7%
2%
18%
82%
46,144
CSO166
752
43%
40%
37%
-13%
23%
60%
36%
55,520,354
CSO167
21
23%
26%
21%
-10%
20%
41%
53%
884,917
CSO172
10
2%
9%
8%
247%
45%
53%
46%
174,925
CSO174
160
18%
18%
17%
-5%
29%
46%
52%
5,380,267
CSO178
39
6%
6%
6%
-13%
13%
18%
81%
431,550
CSO179
223
17%
18%
16%
-4%
19%
35%
64%
7,328,571
CSO180
31
18%
18%
17%
-6%
22%
40%
59%
1,049,697
CSO181
42
2%
3%
4%
77%
6%
10%
90%
361,767
CSO182
172
24%
24%
22%
-9%
31%
53%
43%
7,628,534
CSO183
4
27%
27%
24%
-13%
31%
55%
44%
192,604
CSO184
101
29%
28%
25%
-14%
30%
55%
38%
5,032,782
CSO185
164
22%
22%
21%
-7%
27%
48%
48%
6,741,598
CSO186
4
9%
9%
9%
-3%
10%
19%
80%
78,549
CSO187
6
19%
19%
15%
-23%
15%
29%
69%
176,993
CSO188
14
21%
21%
20%
-4%
41%
62%
37%
560,675
CSO189
1,186
30%
28%
29%
-5%
26%
55%
43%
67,879,983
CSO190
142
12%
11%
13%
4%
20%
33%
66%
3,620,037
CSO191
334
21%
22%
20%
-5%
32%
52%
46%
13,547,611
CSO193
18
32%
31%
29%
-9%
23%
53%
46%
1,043,097
CSO195
6
17%
21%
19%
12%
23%
43%
57%
219,345
CSO196
4
19%
16%
21%
11%
24%
45%
55%
172,167
CSO197
4
9%
13%
12%
29%
19%
30%
69%
86,428
CSO198
4
37%
40%
41%
10%
15%
56%
43%
289,030
CSO199
2
44%
43%
44%
0%
18%
62%
38%
177,633
CSO200
8
56%
52%
47%
-16%
14%
61%
39%
707,037
CSO201
10
13%
14%
17%
28%
18%
35%
64%
338,917
CSO202
6
32%
33%
32%
-2%
13%
45%
54%
374,178
CSO203
8
34%
34%
33%
-2%
19%
52%
47%
559,986
CSO205
8
19%
19%
18%
-8%
37%
54%
42%
298,978
CSO207
2
0%
8%
12%
1%
13%
86%
51,414
CSO208
10
34%
32%
32%
-7%
26%
58%
39%
632,133
CSO210
181
32%
32%
29%
-10%
31%
60%
35%
10,350,702
CSO211
3,709
17%
17%
15%
-7%
23%
39%
57%
113,842,313
Maple St.
675
20%
17%
17%
-16%
23%
40%
58%
22,685,363

Sewersheds (continued)

Benefit
Value ($)
$154
$185,438
$2,956
$584
$17,970
$1,441
$24,477
$3,506
$1,208
$25,479
$643
$16,809
$22,517
$262
$591
$1,873
$226,719
$12,091
$45,249
$3,484
$733
$575
$289
$965
$593
$2,362
$1,132
$1,250
$1,870
$999
$172
$2,111
$34,571
$380,233
$75,769

Value /
Acre
$105.05
$246.71
$140.29
$56.45
$112.00
$36.71
$109.64
$113.47
$28.44
$148.07
$159.06
$166.78
$137.34
$59.19
$96.68
$136.33
$191.09
$84.90
$135.31
$196.11
$129.54
$142.44
$77.86
$269.91
$292.63
$310.76
$113.70
$210.58
$221.05
$118.61
$81.13
$212.22
$190.82
$102.51
$112.17

B11

FINAL DRAFT

Data Tables & Charts

Overlay of Sewersheds and Neighborhoods

hi
O

o

¯

Indiana

Floyd

Clark

io
Oh

r
ve
Ri

er
Riv

Portland
Shawnee

Russell

Chickasaw

Clifton
Heights

Butchertown

Park
Duvalle

University

Hallmark

Cherokee
Seneca

Jacobs

Bonnycastle
Deer
Park

Audubon
Saint Parkway
Joseph Village

Poplar
Level

Audubon
Park
Fairgrounds

Wilder
Park

Highland
Park

Beechmont

Cloverleaf

Camp
Taylor

Highlands Seneca
Douglass Gardens Bowman
Belknap

Kingsley
Strathmoor Hawthorne
StrathmoorVillage
Wellington
Manor
Bon Air
Gardiner
Hayfield
Dundee

Jefferson

Remainder
Standiford
Of City

Klondike

Bashford
Manor

Neighborhoods

CSO Priority by MSD
Low
Medium

Iroquois
Southland
Park

Edgewood

Hikes
Point
Meadowview
Estates
Avondale
Melbourne
Heights

Lane

Prestonia

Southside

Iroquois
Park

Rockcreek
Lexington
Road

Cherokee
Gardens

Cherokee
Triangle

Merriwether
Schnitzelburg

South
Louisville

Wyandotte

Hazelwood

Phoenix
Hill

Shelby
Old
Tyler
Park Germantown
Louisville
Park

Algonquin

Taylor
Berry

Irish
Hill

Smoketown Highlands
Paristown
Jackson
Pointe

Limerick
Park
Hill

Crescent
Hill

Clifton

Central
Business
District

California

Parkland

Brownsboro
Zorn

Moderately High
High

Kenwood
Hill
Auburndale

Kentucky

B12

FINAL DRAFT

Data Tables & Charts

Tree Benefits by Council District
Size
acres

Air Pollution

2012
Canopy

lbs.

value

Total Carbon*
tons

Stormwater

value

gallons

value

Energy
kWhs

value

Property
value

Total
Benefits

Benefits /
Acre

District 1

9,389

27%

184,480

$326,764

331,257

$6,414,243

503,665,733

$1,682,244

2,228,223

$179,951

$5,469,811

$14,073,012

$1,499

District 2

4,986

22%

80,051

$141,793

143,759

$2,783,658

218,645,662

$730,277

1,907,587

$154,054

$3,419,855

$7,229,637

$1,450
$1,440

District 3

4,537

21%

69,195

$122,539

123,860

$2,398,355

187,362,341

$625,790

2,311,806

$186,699

$3,198,419

$6,531,802

District 4

4,153

12%

36,014

$65,144

66,634

$1,290,270

100,820,560

$336,741

1,726,242

$139,414

$1,221,920

$3,053,488

$735

District 5

5,371

23%

92,660

$164,108

164,726

$3,189,652

249,976,802

$834,923

3,200,041

$258,433

$2,983,410

$7,430,525

$1,384

District 6

3,291

18%

42,131

$74,639

76,669

$1,484,569

116,207,196

$388,132

2,624,470

$211,952

$1,732,600

$3,891,892

$1,183

District 7

7,956

40%

227,720

$403,309

413,100

$7,998,980

627,496,537

$2,095,838

3,099,788

$250,340

$10,427,460

$21,175,927

$2,662

District 8

4,322

40%

125,200

$221,737

226,574

$4,387,246

343,591,415

$1,147,595

4,080,870

$329,573

$5,043,212

$11,129,363

$2,575

District 9

6,515

33%

152,840

$270,698

278,776

$5,398,043

423,924,892

$1,415,909

3,980,568

$321,471

$6,255,606

$13,661,728

$2,097

District 10

6,410

25%

118,960

$210,671

210,020

$4,066,686

319,642,574

$1,067,606

2,819,189

$227,676

$4,500,380

$10,073,019

$1,571

District 11

7,032

32%

161,680

$292,429

290,130

$5,617,890

442,786,238

$1,478,906

2,192,613

$177,075

$7,040,259

$14,606,559

$2,077

District 12

8,402

29%

180,920

$319,516

320,330

$6,202,656

486,976,715

$1,626,502

2,095,378

$169,222

$6,090,942

$14,408,839

$1,715

District 13

20,928

48%

730,600

$1,293,914

1,301,612

$25,203,540

1,989,815,876

$6,645,985

2,973,180

$240,113

$21,243,585

$54,627,137

$2,610

District 14

18,013

46%

608,720

$1,078,055

1,089,537

$21,097,071

1,657,891,089

$5,537,356

2,625,073

$212,001

$15,959,913

$43,884,397

$2,436

District 15

4,316

31%

91,632

$175,562

172,139

$3,333,192

262,545,484

$876,902

2,670,190

$215,647

$3,008,409

$7,609,712

$1,763

District 16

16,158

40%

463,340

$820,560

839,688

$16,259,169

1,281,678,562

$4,280,806

2,745,555

$221,731

$18,441,492

$40,023,759

$2,477

District 17

8,916

36%

227,620

$403,954

418,863

$8,110,591

637,595,194

$2,129,568

2,260,489

$182,557

$10,847,858

$21,674,528

$2,431

District 18

7,406

27%

145,860

$258,333

266,412

$5,158,625

405,529,520

$1,354,469

2,478,973

$200,204

$6,866,253

$13,837,883

$1,869

District 19

19,935

39%

578,520

$1,024,610

1,026,341

$19,873,390

1,565,567,728

$5,228,996

3,018,617

$243,783

$20,208,063

$46,578,842

$2,337

District 20

39,330

51%

1,462,300

$2,591,117

2,660,313

$51,512,548

4,028,965,127

$13,456,744

3,144,293

$253,934

$43,342,162

$111,156,504

$2,826

District 21

7,143

16%

81,481

$144,293

144,013

$2,788,586

220,879,597

$737,738

2,347,657

$189,599

$3,491,474

$7,351,690

$1,029

District 22

12,991

35%

333,640

$590,877

597,369

$11,567,060

914,587,930

$3,054,724

1,842,415

$148,793

$11,694,229

$27,055,683

$2,083

District 23

7,988

34%

203,200

$359,841

362,369

$7,016,668

548,372,021

$1,831,563

2,191,365

$176,974

$7,948,402

$17,333,448

$2,170

District 24

6,972

29%

145,400

$257,499

261,045

$5,054,704

397,738,078

$1,328,445

2,257,589

$182,321

$5,873,061

$12,696,030

$1,821

District 25

7,702

45%

250,800

$444,206

452,451

$8,760,968

687,575,820

$2,296,503

2,609,323

$210,728

$10,096,286

$21,808,692

$2,832

4,160

24%

74,817

$132,494

133,260

$2,580,368

202,009,584

$674,712

2,217,831

$179,111

$3,491,620

$7,058,304

$1,697

District 26

* Carbon includes annual benefits and carbon stored over lifetime of canopy.

B13

FINAL DRAFT

Data Tables & Charts

Canopy & Socioeconomic Trends: Scatterplot Charts
Relationship Between

Relationship Between

Census Tract Data Point

Canopy Trend Line

80
70
Canopy %

Canopy %

60
50
40
30
20
10
0

2,000

4,000

6,000

8,000

Ce
80

70

70

60

60

50

50

40
30

20
10
0
0

20

40
60
% of all Households Owner-Occupied

80

100

Population Density (Residents per Square Mile)

Relationship Between

Relationship Between
Relationship Between

Canopy & Renter-Occupied Properties

Canopy
& Owner-Occupied
Canopy
& Household
Income Properties

70

50

Canopy %

Canopy %

60

40
30

70

70

60

60

50

50

Census Tract Data Point

Canopy %

80

80

40
30

30

20

20

10

10

10

0

0

0
25,000
0

0

50,000 20

75,000
125,000
40100,000
60
% of all
Households
Median Household
Income
($) Owner-Occupied

150,000
80

100

Canopy Trend Line

40

20

30

10

10,000

Census Tract Data Point
Canopy Trend Line
Census Tract Data Point
Canopy Trend Line
80

40

20

0

0

Canopy Trend Line

80

Canopy %

Census Tract Data Point

Canopy

Canopy & Owner-Occupied Properties

Canopy & Population Density

0

20

40

60

% of all Households Renter-Occupied

80

100

0

20

B14

FINAL DRAFT

Data Tables & Charts

Relationship Between

Relationship Between

Canopy & Age of Housing

Canopy & Housing Values

by Year Built

After 2000

80s & 90s

60s and 70s

40s and 50s

Before 1940

Under $50k

50

$50-$100k

$100-$250k

$250-$500k

Over $500k

60

Canopy %

Canopy %

50

40

30

40
30
20

20

10

10
0

Low

Med

High

% of Housing in Age Range

Relationship Between

Canopy & Age Groups
Under 18
45 to 64

50

18 to 24
Over 65

25 to 44

Canopy %

40
30
20
10
0

Low

Med

% of Population within Age Group

High

Low

Med

% of Housing in Value Range

High

10

10
0

0
0

10

20
30
% of Residents without a HS Degree

40

50

Axis Title
0

10

20

30

40

50

60

70

% of Residents with a HS Degree

B15

FINAL DRAFT

SOMEWHAT AGGREGATED:

Data Tables & Charts

Relationship Between

Relationship Between

Education & Canopy: College Educated (All Levels)

Education & Canopy: High School Diploma or Less

Census Tract Data Point

Canopy Trend Line

80

70

70

60

60

50

50

%Canopy

%Canopy

Census Tract Data Point
80

40
30

AGGREGATED:

40
30

20

20

10

10

0

0

10

20

30

40

50

% of Residents with a High School Diploma or Less

60

70

80

Canopy Trend Line

0

0

10

20

30

40

50

% of Residents with College Education (All Levels)

60

70

80

B16

FINAL DRAFT

Data Tables & Charts

Scenarios for Future Canopy
#

SCENARIO 0: No Action
Starting Canopy
Acres: 94,462
Year 1
Year 2
Year 3
Year 4
Year 5
Year 6
Year 7
Year 8
Year 9
Year 10
Year 11
Year 12
Year 13
Year 14
Year 15
Year 16
Year 17
Year 18
Year 19
Year 20
Year 21
Year 22
Year 23
Year 24
Year 25
Year 26
Year 27
Year 28
Year 29
Year 30
Year 31
Year 32
Year 33
Year 34
Year 35
Year 36
Year 37
Year 38
Year 39
Year 40
TOTALS

Acres
Planted
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
acres
planted

Canopy
Acres
Resulting Resulting
Lost
Canopy
UTC %
820
93,642
37%
820
92,822
36%
820
92,002
36%
820
91,182
36%
820
90,362
36%
820
89,542
35%
820
88,722
35%
820
87,902
35%
820
87,082
34%
820
86,262
34%
820
85,442
34%
820
84,622
33%
820
83,802
33%
820
82,982
33%
820
82,162
32%
820
81,342
32%
820
80,522
32%
820
79,702
31%
820
78,882
31%
820
78,062
31%
820
77,242
30%
820
76,422
30%
820
75,602
30%
820
74,782
29%
820
73,962
29%
820
73,142
29%
820
72,322
28%
820
71,502
28%
820
70,682
28%
820
69,862
27%
820
69,042
27%
820
68,222
27%
820
67,402
26%
820
66,582
26%
820
65,762
26%
820
64,942
26%
820
64,122
25%
820
63,302
25%
820
62,482
25%
820
61,662
24%
32,800
acres lost

SCENARIO 1a: Achieveing No Net Loss by Planting
Only
Canopy
Resulting
Acres
Acres
Resulting Future
Trees Planted
Planted
Lost
Canopy UTC %*
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
54,120
820
820
94,462
37%
2,164,800
32,800
32,800
trees
acres
acres lost
planted

SCENARIO 1b: Achieving No Net Loss by Planting
AND Loss Reduction
Canopy
Resulting
Trees
Acres
Acres
Resulting Future
Planted
Planted
Lost
Canopy UTC %*
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
27,060
410
410
94,462
37%
1,082,400
16,400
16,400
trees
acres
acres lost
planted

* Resulting Future UTC %: Scenario spans a forty year time period to allow for trees planted in the first ten years to reach full canopy levels. UTC is thus
listed each year as a future canopy of acres planted.

SCENARIO 2a: Achieving 40% Canopy by Planting
Only
Canopy
Resulting
Trees
Acres
Acres
Resulting Future
Planted
Planted
Lost
Canopy UTC %*
102,432
1,552
820
95,194
37%
102,432
1,552
820
95,926
38%
102,432
1,552
820
96,658
38%
102,432
1,552
820
97,390
38%
102,432
1,552
820
98,122
39%
102,432
1,552
820
98,854
39%
102,432
1,552
820
99,586
39%
102,432
1,552
820
100,318
39%
102,432
1,552
820
101,050
40%
102,432
1,552
820
101,782
40%
54,120
820
820
101,782
40%
54,120
820
820
101,782
40%
54,120
820
820
101,782
40%
54,120
820
820
101,782
40%
54,120
820
820
101,782
40%
54,120
820
820
101,782
40%
54,120
820
820
101,782
40%
54,120
820
820
101,782
40%
54,120
820
820
101,782
40%
54,120
820
820
101,782
40%
54,120
820
820
101,782
40%
54,120
820
820
101,782
40%
54,120
820
820
101,782
40%
54,120
820
820
101,782
40%
54,120
820
820
101,782
40%
54,120
820
820
101,782
40%
54,120
820
820
101,782
40%
54,120
820
820
101,782
40%
54,120
820
820
101,782
40%
54,120
820
820
101,782
40%
54,120
820
820
101,782
40%
54,120
820
820
101,782
40%
54,120
820
820
101,782
40%
54,120
820
820
101,782
40%
54,120
820
820
101,782
40%
54,120
820
820
101,782
40%
54,120
820
820
101,782
40%
54,120
820
820
101,782
40%
54,120
820
820
101,782
40%
54,120
820
820
101,782
40%
2,647,920
40,120
32,800
trees
acres
acres lost
planted

B17

FINAL DRAFT

Data Tables & Charts

Scenarios for Future Canopy (continued)

Starting Canopy
Acres: 94,462
Year 1
Year 2
Year 3
Year 4
Year 5
Year 6
Year 7
Year 8
Year 9
Year 10
Year 11
Year 12
Year 13
Year 14
Year 15
Year 16
Year 17
Year 18
Year 19
Year 20
Year 21
Year 22
Year 23
Year 24
Year 25
Year 26
Year 27
Year 28
Year 29
Year 30
Year 31
Year 32
Year 33
Year 34
Year 35
Year 36
Year 37
Year 38
Year 39
Year 40
TOTALS

SCENARIO 2b: Achieving 40% Canopy by Planting
AND Loss Reduction
Canopy Resulting Resulting
Trees
Acres
Acres
Canopy
Future
Planted
Lost
Acres
UTC %*
Planted
75,372
1,142
410
95,194
37%
75,372
1,142
410
95,926
38%
75,372
1,142
410
96,658
38%
75,372
1,142
410
97,390
38%
75,372
1,142
410
98,122
39%
75,372
1,142
410
98,854
39%
75,372
1,142
410
99,586
39%
75,372
1,142
410
100,318
39%
75,372
1,142
410
101,050
40%
75,372
1,142
410
101,782
40%
27,060
410
410
101,782
40%
27,060
410
410
101,782
40%
27,060
410
410
101,782
40%
27,060
410
410
101,782
40%
27,060
410
410
101,782
40%
27,060
410
410
101,782
40%
27,060
410
410
101,782
40%
27,060
410
410
101,782
40%
27,060
410
410
101,782
40%
27,060
410
410
101,782
40%
27,060
410
410
101,782
40%
27,060
410
410
101,782
40%
27,060
410
410
101,782
40%
27,060
410
410
101,782
40%
27,060
410
410
101,782
40%
27,060
410
410
101,782
40%
27,060
410
410
101,782
40%
27,060
410
410
101,782
40%
27,060
410
410
101,782
40%
27,060
410
410
101,782
40%
27,060
410
410
101,782
40%
27,060
410
410
101,782
40%
27,060
410
410
101,782
40%
27,060
410
410
101,782
40%
27,060
410
410
101,782
40%
27,060
410
410
101,782
40%
27,060
410
410
101,782
40%
27,060
410
410
101,782
40%
27,060
410
410
101,782
40%
27,060
410
410
101,782
40%
1,565,520
23,720
16,400
trees
acres
acres lost
planted

SCENARIO 3a: Achieving 45% Canopy by Planting
SCENARIO 3b: Achieving 45% Canopy by Planting
Only
AND Loss Reduction
Canopy
Resulting
Canopy
Resulting
Trees
Acres
Resulting Future
Acres
Resulting Future
Acres
Acres
Canopy UTC %*
Planted
Lost
Canopy UTC %* Trees Planted Planted
Lost
Planted
186,384
2,824
820
96,466
38%
159,324
2,414
410
97,198
38%
186,384
2,824
820
98,470
39%
159,324
2,414
410
99,202
39%
186,384
2,824
820
100,474
39%
159,324
2,414
410
101,206
40%
186,384
2,824
820
102,478
40%
159,324
2,414
410
103,210
41%
186,384
2,824
820
104,482
41%
159,324
2,414
410
105,214
41%
186,384
2,824
820
106,486
42%
159,324
2,414
410
107,218
42%
186,384
2,824
820
108,490
43%
159,324
2,414
410
109,222
43%
186,384
2,824
820
110,494
43%
159,324
2,414
410
111,226
44%
186,384
2,824
820
112,498
44%
159,324
2,414
410
113,230
45%
186,384
2,824
820
114,502
45%
159,324
2,414
410
115,234
45%
54,120
820
820
114,502
45%
27,060
410
410
115,234
45%
54,120
820
820
114,502
45%
27,060
410
410
115,234
45%
54,120
820
820
114,502
45%
27,060
410
410
115,234
45%
54,120
820
820
114,502
45%
27,060
410
410
115,234
45%
54,120
820
820
114,502
45%
27,060
410
410
115,234
45%
54,120
820
820
114,502
45%
27,060
410
410
115,234
45%
54,120
820
820
114,502
45%
27,060
410
410
115,234
45%
54,120
820
820
114,502
45%
27,060
410
410
115,234
45%
54,120
820
820
114,502
45%
27,060
410
410
115,234
45%
54,120
820
820
114,502
45%
27,060
410
410
115,234
45%
54,120
820
820
114,502
45%
27,060
410
410
115,234
45%
54,120
820
820
114,502
45%
27,060
410
410
115,234
45%
54,120
820
820
114,502
45%
27,060
410
410
115,234
45%
54,120
820
820
114,502
45%
27,060
410
410
115,234
45%
54,120
820
820
114,502
45%
27,060
410
410
115,234
45%
54,120
820
820
114,502
45%
27,060
410
410
115,234
45%
54,120
820
820
114,502
45%
27,060
410
410
115,234
45%
54,120
820
820
114,502
45%
27,060
410
410
115,234
45%
54,120
820
820
114,502
45%
27,060
410
410
115,234
45%
54,120
820
820
114,502
45%
27,060
410
410
115,234
45%
54,120
820
820
114,502
45%
27,060
410
410
115,234
45%
54,120
820
820
114,502
45%
27,060
410
410
115,234
45%
54,120
820
820
114,502
45%
27,060
410
410
115,234
45%
54,120
820
820
114,502
45%
27,060
410
410
115,234
45%
54,120
820
820
114,502
45%
27,060
410
410
115,234
45%
54,120
820
820
114,502
45%
27,060
410
410
115,234
45%
54,120
820
820
114,502
45%
27,060
410
410
115,234
45%
54,120
820
820
114,502
45%
27,060
410
410
115,234
45%
54,120
820
820
114,502
45%
27,060
410
410
115,234
45%
54,120
820
820
114,502
45%
27,060
410
410
115,234
45%
3,487,440
52,840
32,800
2,405,040
36,440
16,400
trees
acres
acres lost
trees
acres
acres lost
planted
planted

Appendix
C
FINAL DRAFT
Other Information
Sustain Louisville Goals
(target date in parenthesis)
Energy
1. Decrease energy use citywide per capita by 25% (2025)
2. Decrease energy use in city-owned buildings by 30% (2018)
Environment
3. Mitigate the risk of climate change impacts (2018)
4. Achieve and exceed National Ambient Air Quality Standards
(Ongoing)
5. Improve waterway quality (2018)
6. Increase recycling citywide by 25% (2015)
7. Achieve 90% residential recycling participation (2025)
8. Divert 50% of solid waste away from the landfill by 2025 and 90%
by 2042 (2025)
Transportation
9. Decrease transportation-related greenhouse gas emissions by
20% (2020)
10. Reduce vehicle miles traveled by 20% (2025)
Economy
11. Provide opportunities for clean economy organizations and
innovators and develop a qualified workforce to support it (2015)
12. Expand the local food system by 20% (2018)
Community
13. Increase access to healthy foods by 20% (2018)
14. Increase opportunities for active living (2015)
15. Incorporate sustainability into the Land Development Code and
the Comprehensive Plan (2015)

16. Replace and reforest parks property and provide nature-based
recreation (2018)
17. Expand green infrastructure incentives citywide (2018)
18. Establish a robust urban tree canopy and implement strategies to
mitigate the urban heat island effect (2018)
Engagement
19. Engage the community in sustainability practices and principles
(Ongoing)

C2

FINAL DRAFT

Other Information

Glossary
bare soil land cover: The land cover areas
mapped as bare soil typically include vacant
lots, construction areas, and baseball fields.

land cover: Physical features on the earth
mapped from satellite or aerial imagery such
as bare soils, canopy, impervious, pervious, or
water.

right-of-way (ROW): A strip of land generally
owned by a public entity over which facilities,
such as highways, railroads, or power lines, are
built.

canopy: Branches and foliage which make up a mortality: tree loss from insects, disease,
natural tree decline/death, severe weather
tree’s crown.
events, removals by human activities, etc.

street tree: A street tree is defined as a tree
within the right-of-way.

canopy cover: As seen from above, it is the area
open water land cover: The land cover areas
of land surface that is covered by tree canopy.
mapped as water typically include lakes,
canopy spread: A data field that estimates the oceans, rivers, and streams.

species: Fundamental category of taxonomic
classification, ranking below a genus or
subgenus.

width of a tree’s canopy in five-foot increments.
existing UTC: The amount of tree canopy
present within the study boundary.
geographic information systems (GIS): A
technology that is used to view and analyze
data from a geographic perspective. GIS
links location to information (such as people
to addresses, buildings to parcels, or streets
within a network) and layers that information
to give you a better understanding of how it all
interrelates.

pervious land cover: The vegetative area that
allows rainfall to infiltrate the soil and typically
includes parks, golf courses, residential areas.
possible UTC: The amount of land that is
theoretically available for the establishment of
tree canopy within the study boundary. This
includes all pervious and bare soil surfaces.

tree: A tree is defined as a perennial woody plant
that may grow more than 20 feet tall.
tree benefit: An economic, environmental, or
social improvement that benefited the community
and resulted mainly from the presence of a tree.
Has associated value.

urban forest: All of the trees within a
municipality or a community. This can include the
rate of change: percentage change, comparing trees along streets or rights-of-way, parks and
old values to current values using the following greenspaces, and forests.
value - older value
x 100
equation: current older
value
urban tree canopy (UTC) assessment: A
study performed of land cover classes to gain
realistic
plantable
areas
(RPA):
The
amount
greenspace: A term used in land use planning
an understanding of the tree canopy coverage,
and conservation to describe protected areas of of land that is realistically available for the
Typically performed using aerial photographs,
establishment
of
tree
canopy
within
the
town
undeveloped landscapes.
GIS data, or LIDAR.
boundary. This includes all pervious and bare
soil
surfaces
with
specified
land
uses.
impervious land cover: The area that does not
allow rainfall to infiltrate the soil and typically
includes buildings, parking lots, and roads.

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